PyTorch Jobs in New York.

SC

Scale AI

View all jobs →

SC

Senior / Staff Machine Learning Research Scientist, Agents

Scale AI · San Francisco, CA; Seattle, WA; New York, NY

Apply now

Research San Francisco, CA Posted May 8, 2026

About Scale

At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations.

About the ACE team

The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more.

About This Role

This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable solutions.

Ideally you’d have:

Practical experience working with LLMs, with proficiency in frameworks like Pytorch, Jax, or Tensorflow. You should also be adept at interpreting research literature and quickly turning new ideas into prototypes.
A track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.)
At least three years of experience addressing sophisticated ML problems, either in a research setting or product development.
Strong written and verbal communication skills and the ability to operate cross-functionally.

Nice to have:

Hands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/Jax.
Hands-on experience and publications in building applications and evaluations related to AI agents such as tool-use, text2SQL, browser agents, coding agents and GUI agents.
Hands-on experience with agent frameworks such as OpenHands, Swarm, LangGraph, etc.
Familiarity with agentic reasoning methods such as STaR and PLANSEARCH
Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.

Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We will not ask any LeetCode-style questions.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:

$259,200—$324,000 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

Ready to apply?

SC

Scale AI

View all jobs →

SC

Senior Machine Learning Engineer - Model Evaluations, Public Sector

Scale AI · San Francisco, CA; St. Louis, MO; New York, NY; Washington, DC

Apply now

Public Sector Engineering Washington, DC Posted May 8, 2026

Senior Machine Learning Engineer - Model Evaluations, Public Sector

The Public Sector ML team at Scale deploys advanced AI systems—including LLMs, agentic models, and multimodal pipelines—into mission-critical government environments. We build evaluation frameworks that ensure these models operate reliably, safely, and effectively under real-world constraints. As an ML Engineer, you will design, implement, and scale automated evaluation pipelines that help customers trust and operationalize advanced AI systems across defense, intelligence, and federal missions.

You will:

Develop and maintain automated evaluation pipelines for ML models across functional, performance, robustness, and safety metrics, including LLM-judge–based evaluations.
Design test datasets and benchmarks to measure generalization, bias, explainability, and failure modes.
Build evaluation frameworks for LLM agents, including infrastructure for scenario-based and environment-based testing.
Conduct comparative analyses of model architectures, training procedures, and evaluation outcomes.
Implement tools for continuous monitoring, regression testing, and quality assurance for ML systems.
Design and execute stress tests and red-teaming workflows to uncover vulnerabilities and edge cases.
Collaborate with operations teams and subject matter experts to produce high-quality evaluation datasets.
Comfortable with light travel (approximately 10%) for customer interaction and team needs.

This role will require an active security clearance or the ability to obtain a security clearance.

Ideally you’d have:

Experience in computer vision, deep learning, reinforcement learning, or NLP in production settings.
Strong programming skills in Python; experience with TensorFlow or PyTorch.
Background in algorithms, data structures, and object-oriented programming.
Experience with LLM pipelines, simulation environments, or automated evaluation systems.
Ability to convert research insights into measurable evaluation criteria.

Nice to haves:

Graduate degree in CS, ML, or AI.
Cloud experience (AWS, GCP) and model deployment experience.
Experience with LLM evaluation, CV robustness, or RL validation.
Knowledge of interpretability, adversarial robustness, or AI safety frameworks.
Familiarity with ML evaluation frameworks and agentic model design.
Experience in regulated, classified, or mission-critical ML domains.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:

$240,450—$300,300 USD

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of Washington DC, Texas, Colorado, Hawaii is:

$216,300—$269,850 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

Ready to apply?

SC

Scale AI

View all jobs →

SC

Tech Lead Manager- MLRE, ML Systems

Scale AI · San Francisco, CA; New York, NY

Apply now

Research San Francisco, CA Posted May 8, 2026

Scale's LLM post-training platform team builds our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline.

Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimizing the platform to enable our next generation LLM training, inference and data curation.

If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you!

You will:

Build, profile and optimize our training and inference framework.
Collaborate with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation.
Research and integrate state-of-the-art technologies to optimize our ML system.

Ideally you’d have:

Passionate about system optimization
Experience with multi-node LLM training and inference
Experience with developing large-scale distributed ML systems
Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.
Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc.
Strong written and verbal communication skills to operate in a cross functional team environment.

Nice to haves:

Demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:

$264,800—$331,000 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

Ready to apply?

SC

Scale AI

View all jobs →

SC

ML Research Engineer, ML Systems

Scale AI · San Francisco, CA; Seattle, WA; New York, NY

Apply now

Research San Francisco, CA Posted May 8, 2026

Scale’s ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality.

Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation.

If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you!

You will:

Build, profile and optimize our training and inference framework
Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation
Research and integrate state-of-the-art technologies to optimize our ML system

Ideally you’d have:

Strong excitement about system optimization
Experience with multi-node LLM training and inference
Experience with developing large-scale distributed ML systems
Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc.
Strong written and verbal communication skills and the ability to operate in a cross functional team environment

Nice to haves:

Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:

$189,600—$237,000 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

Ready to apply?

SC

Scale AI

View all jobs →

SC

Senior Machine Learning Engineer, Public Sector

Scale AI · San Francisco, CA; New York, NY; Washington, DC

Apply now

Public Sector Engineering Washington, DC Posted May 8, 2026

The goal of a Senior Machine Learning Engineer at Scale is to leverage techniques in the fields of generative AI, computer vision, reinforcement learning, and agentic AI to improve Scale's products and customer experience in production environments. Our machine learning engineers take advantage of robust internal infrastructure and unique access to massive datasets to deliver improvements to our customers.

Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like Donovan and Thunderforge. Our work spans multiple modalities, with a strong focus on both large language models and computer vision. On the LLM side, we are developing agentic systems that help solve complex operational and planning challenges for government partners. This includes building agent frameworks that integrate with custom retrieval pipelines and production APIs, as well as evaluation tools to benchmark and refine agent behavior. We're also advancing research in areas like reinforcement learning for agentic LLMs, with successful deployment into real-world operational environments. On the computer vision front, we're training advanced models to increase labeling throughput and automate perception tasks. Our efforts include building large-scale fine-tuning pipelines, training models across multiple modalities, and developing generalizable vision foundation models to support a wide range of defense applications.

You will:

Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers
Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics
Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines
Work with massive datasets to develop both generic models as well as fine tune models for specific products
Build scalable machine learning infrastructure to automate and optimize our ML services
Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations
Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment
Comfortable with light travel (approximately 10%) for customer interaction and team needs
This role will require an active security clearance or the ability to obtain a security clearance

Ideally You’d Have:

Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment
Solid background in algorithms, data structures, and object-oriented programming
Strong programing skills in Python, experience in Tensorflow or PyTorch

Nice to Haves:

Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization
Experience working with cloud platforms (eg. AWS or GCP) and deploying machine learning models in cloud environments
Experience with computer vision, generative AI models, large language models, or agentic systems
Familiarity with ML evaluation frameworks and agentic model design

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:

$240,450—$300,300 USD

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of Washington DC, Texas, Colorado, Hawaii is:

$216,300—$269,850 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

Ready to apply?

SC

Scale AI

View all jobs →

SC

Senior AI Infrastructure Engineer - Training Platform

Scale AI · San Francisco, CA; Seattle, WA; New York, NY

Apply now

Research New York, NY San Francisco, CA Posted May 8, 2026

As a Software Engineer on the Machine Learning Infrastructure team, you will build the "Operating System" for our large-scale GPU clusters. You will architect a high-performance training platform that handles the immense complexity of multi-thousand GPU workloads, ensuring every cycle is used efficiently. Your work directly determines the velocity at which our researchers can train and iterate on the world’s most advanced models.

The ideal candidate is a systems expert who thrives on solving the orchestration, networking, and reliability challenges that emerge at massive scale. You will partner closely with researchers to build a seamless, resilient environment that transforms raw compute into breakthrough AI.

You will:

Architect and scale a multi-tenant orchestration layer that abstracts away the complexity of GPU clusters, ensuring high utilization and seamless job recovery.
Design and implement scheduling primitives to optimize the lifecycle of training jobs.
Develop deep observability and automated health-checking into the training stack to proactively identify and isolate hardware failures
Evaluate and integrate emerging technologies in the CNCF and AI ecosystem (e.g. Ray, Kueue), making data-driven build vs. buy decisions that balance velocity with long-term maintainability.
Work closely with Finance and Procurement teams to drive our capacity planning process.
Participate in our team’s on call process to ensure the availability of our services.
Own projects end-to-end, from requirements, scoping, design, to implementation, in a highly collaborative and cross-functional environment.

Ideally you'd have:

5+ years of experience in backend or infrastructure engineering, with at least 2 years focused on orchestrating ML workloads at scale (100+ GPU nodes).
Strong programming skills in one or more languages (e.g. Python, Go, Rust, C++)
Experience with complex compute management systems that cover queueing, quotas, preemption, and gang scheduling.
Experience with distributed training infrastructure, such as EFA, Infiniband, and topology-aware scheduling.
Experience with distributed storage systems (e.g. Lustre, S3) as they relate to training throughput
Expert-level knowledge of Kubernetes internals (Custom Resources, Operators, Admission Controllers) and how they interact with device plugins for specialized hardware.
Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform).
Proven ability to solve complex problems and work independently in fast-moving environments.

Nice to haves:

Experience with distributed training techniques such as DeepSpeed, FSDP, etc.
Experience with the NVIDIA software and hardware stack (CUDA, NCCL)
Experience with PyTorch
Familiarity with post-training algorithms such as GRPO, and with Reinforcement Learning

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:

$216,000—$270,000 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

Ready to apply?

SC

Scale AI

View all jobs →

SC

Machine Learning Research Scientist, Reasoning

Scale AI · San Francisco, CA; Seattle, WA; New York, NY

Apply now

Research San Francisco, CA Posted May 8, 2026

About Scale

At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, fueling the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re amplifying access to high-quality data to drive progress toward Artificial General Intelligence (AGI). Building on our history of model evaluation with enterprise and government customers, we are expanding our capabilities to set new standards for both public and private evaluations.

About This Role

This role operates at the forefront of AI research and real-world implementation, with a strong focus on reasoning within large language models (LLMs). The ideal candidate will study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents. You will play a key role in shaping Scale’s data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning. Success in this role requires a deep understanding of LLMs, planning algorithms, and novel approaches to agentic reasoning, as well as creativity in tackling challenges related to data generation, model interaction, and evaluation. You will contribute to impactful research on language model reasoning, collaborate with external researchers, and work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions.

Ideally, you’d have:

Practical experience working with LLMs, with proficiency in frameworks like PyTorch, JAX, or TensorFlow. You should also be skilled at rapidly interpreting research literature and turning new ideas into working prototypes.
A track record of published research in top ML and NLP venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, CoLLM, etc.).
At least three years of experience solving complex ML challenges, either in a research setting or product development, particularly in areas related to LLM capabilities and reasoning.
Strong written and verbal communication skills, along with the ability to work effectively across teams.

Nice to have:

Hands-on experience fine-tuning open-source LLMs or leading bespoke LLM fine-tuning projects using PyTorch/JAX.
Research and practical experience in building applications and evaluations related to LLM-based agents, including tool-use, text-to-SQL, browser agents, coding agents, and GUI agents.
Experience with agent frameworks such as OpenHands, Swarm, LangGraph, or similar.
Familiarity with advanced agentic reasoning techniques such as STaR and PLANSEARCH.
Proficiency in cloud-based ML development, with experience in AWS or GCP environments.

Our research interviews are designed to assess candidates' ability to prototype and debug ML models, their depth of understanding in research concepts, and their alignment with our organizational culture. We do not conduct LeetCode-style problem-solving assessments.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:

$252,000—$315,000 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

Ready to apply?

SC

Scale AI

View all jobs →

SC

Machine Learning Research Engineer, GenAI Applied ML

Scale AI · San Francisco, CA; New York, NY

Apply now

Research New York, NY San Francisco, CA Posted May 8, 2026

About This Role

Lead applied ML engineering on Scale's Applied ML team, powering data infrastructure for leading agentic LLMs (ChatGPT, Gemini, Llama). You will build scalable multi-agent systems to validate agentic reasoning and behaviors, scale human expertise, and drive research into real-world agent reliability failures despite strong benchmarks, shipping production fixes.

Ideal for exceptional engineers with deep research rigor and a relentless focus on practical, high-impact systems. You will iterate rapidly with data, leverage AI tools to accelerate development, and collaborate tightly across engineering, product, and research.

If you excel at turning frontier agent research into reliable deployed systems, we want to hear from you.

You will:

Build and deploy multi-agent systems for agentic reasoning validation
Develop pipelines to detect errors and scale human judgment
Combine classical ML, LLMs, and multi-agent techniques for reliability
Lead research into agent failure modes and ship fixes
Use AI tools to speed prototyping and iteration
Build data-driven evaluations and deploy rapid improvements
Integrate systems into Scale's platform

Ideally You’ll Have:

PhD or MSc in Computer Science, Mathematics, Statistics, or related field
3+ years shipping scaled production ML systems
Demonstrated real-world impact
Mastery of PyTorch, TensorFlow, JAX, or scikit-learn
Deep expertise in agentic LLMs and multi-agent systems
Strong software engineering and microservices (AWS/GCP)
Rapid, data-driven iteration
Proficiency using AI tools to accelerate work
Strong research depth with practical bias
Excellent cross-functional communication

Nice to Have:

Experience prototyping agent evaluation/reliability systems
Human-in-the-loop or annotation pipeline work
Open-source contributions in agents, evaluation, or alignment
Publications on agent reliability (NeurIPS, ICML, ICLR)

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:

$189,600—$237,000 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

Ready to apply?

SC

Scale AI

View all jobs →

Senior Value Engineer - Life Sciences

Celonis · New York, US, New York

Apply now

Value Engineering New York, US, New York Posted May 8, 2026

Celonis is the global leader in Process Intelligence and the pioneer of Process Mining technology. As one of the world’s fastest-growing enterprise SaaS companies, we are changemakers pushing the boundaries of what’s possible. We invest heavily in advanced AI capabilities—specifically our Process Intelligence Graph—to turn data insights into immediate business action. We believe there is a massive opportunity to unlock global productivity and sustainability by placing intelligence at the core of every business process. Join our mission to make processes work for people, companies, and the planet.

Role Description

As a Senior Value Engineer specializing in the Life Sciences, you are pushing the envelope in solving business-critical problems for the world's largest, most diversified life science organizations. You will be working intimately with this strategic client, understanding their uniquely complex objectives—spanning from logistics to the precision distribution of advanced products—and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with top AI and ML technology partners (e.g., Microsoft, OpenAI, Databricks)..

With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands the intricate realities of our customers’ supply chain networks and enables them to industrialize AI. This unlocks real ROI on AI deployments at scale, ensuring life-saving products reach patients faster and safer. There is no AI without PI. You will prototype these solutions, demonstrate their value to Chief Supply Chain Officers (CSCOs) and operational leaders, and ensure successful implementation, adoption, and value realization to increase the footprint of Celonis across the life sciences sector.

Key Responsibilities

AI Discovery & Solutioning: Understand the client's overarching AI strategy and the distinct supply chain challenges across both their MedTech portfolios (e.g., mitigating global raw material shortages, optimizing supply chains, managing inventories, or accelerating quality batch releases). As a Celonis product and life sciences domain expert, translate these complex, multi-tiered logistics requirements into innovative AI solutions that drive measurable impact..
Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the pre-sales cycle, and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds in the supply chain are successfully reached.
Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude, and don’t shy away from complex, fragmented supply chain networks. Leverage cutting-edge AI technologies to rapidly build creative prototypes in customer hackathons, solving critical pain points in planning, sourcing, manufacturing, and distribution.
Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale, enabling a fundamental shift from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform (e.g., autonomous inventory rebalancing or intelligent shipment exception handling).
Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. This includes architecting and delivering secure, scalable LLM/agent systems with RAG, tools, and guardrails, while seamlessly integrating with enterprise ERPs (e.g., SAP), Quality Management Systems (QMS), and strict regulatory frameworks (FDA, EMA, GxP).
Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for the Life Sciences Supply Chain, scaling knowledge across the organization regarding pharmaceutical manufacturing and logistics processes.

Requirements

5+ years of experience leading technical pre-sales and post-sales engagements specifically within Life Sciences, Pharmaceutical, or MedTech supply chains. This includes defining AI roadmaps, building compelling ROI/TCO business cases, and guiding technical implementations through to value realization.
Deep understanding of supply chain business processes native to Life Sciences (such as Sales & Operations Planning (S&OP), Procure-to-Pay, Track & Trace, Cold Chain Management, or Quality Control/Batch Release) with the ability to translate high-level business needs into specific AI use cases.
Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases (e.g., intelligent chatbots for supplier collaboration, automated extraction of data from complex customs or quality documents).
Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies for handling massive, siloed supply chain datasets.
Strong presentation skills to both internal and external stakeholders (including supply chain executives and IT leaders), whether leading technical whiteboarding sessions or formal readouts and demos.
Bachelor’s Degree required; Master's Degree in computer science, supply chain management, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to Have (Big Plus)

Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations suited for highly regulated (GxP) life sciences environments.
Familiarity with life sciences supply chain data standards and systems (e.g., GS1 EPCIS for traceability, SAP APO/IBP, Kinaxis).
Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex).

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

The base salary range below is for the role in the specified location, based on a Full Time Schedule.

Total compensation package will include base salary + bonus/commission + equity + benefits (health, dental, life, 401k, and paid time off). Please note that the base salary range is a guideline, and that the actual total compensation offer will be determined based on various factors, including, but not limited to, applicant's qualifications, skills, experiences, and location.

The base salary range below is for the role in New York, based on a Full Time Schedule.

$131,000—$154,000 USD

What Celonis can offer you:

Pioneer Innovation: Work with the global leader in Process Mining and the Process Intelligence Graph to shape the future of AI-driven business operations.
Ownership from Day 1: Every full-time "Celonaut" is an owner, receiving Restricted Stock Units (RSUs) and merit-based refresh grants.
Unrivaled Family Support: Benefit from our inclusive parental leave policy—24 weeks of fully paid leave for primary carers and 12 weeks for supporting carers, available from your first day of employment.
Work-Life Integration: Enjoy Unlimited PTO (in applicable regions) and generous PTO globally, as well as a flexible hybrid work model that balances remote focus with vibrant office collaboration.
Continuous Growth: Elevate your skills through our 70-20-10 learning framework, mentorship programs, and access to a dedicated learning platform.
Holistic Well-being: Prioritize your health with subsidized Wellhub memberships, mental health counseling, and dedicated "Wellness Weeks" that prioritize work/life balance.
Drive Sustainability: Participate in annual Impact Days, where you receive paid time off to volunteer for community and environmental causes with your local office, or virtually.
Global Inclusion & Belonging: Find community through our Inclusion Think Tank and participate in our annual Inclusion Days, ensuring every voice is heard and valued.
Value-Driven Impact: Join a mission-led organization where our core values—Live for Customer Value, The Best Team Wins, We Own It, and Earth Is Our Future—drive every decision.

About Us:

Celonis makes processes work — for people, companies, and the planet. Powered by process mining and AI, the Celonis Process Intelligence Platform integrates process data and business context to create a living digital twin of business operations. We enable thousands of companies worldwide to understand how their business actually runs and, together with their partners, build intelligent solutions that transform and continuously improve the way they operate — unlocking billions in value. Celonis is headquartered in Munich, Germany, and New York City, USA, with more than 20 offices worldwide.

Get familiar with the Celonis Process Intelligence Platform by watching this video.

Celonis Inclusion Statement:

At Celonis, we believe our people make us who we are and that “The Best Team Wins”. We know that the best teams are made up of people who bring different perspectives to the table. And when everyone feels included, able to speak up and knows their voice is heard - that's when creativity and innovation happen.

Your Privacy:

Any information you submit to Celonis as part of your application will be processed in accordance with Celonis’ Accessibility and Candidate Notices

By submitting this application, you confirm that you agree to the storing and processing of your personal data by Celonis as described in our Privacy Notice for the Application and Hiring Process.

Please be aware of common job offer scams, impersonators and frauds. Learn more here.

Ready to apply?

Celonis

View all jobs →

Senior Value Engineer - Energy Industry

Celonis · New York, US, New York

Apply now

Value Engineering New York, US, New York Posted May 8, 2026

Celonis is the global leader in Process Intelligence and the pioneer of Process Mining technology. As one of the world’s fastest-growing enterprise SaaS companies, we are changemakers pushing the boundaries of what’s possible. We invest heavily in advanced AI capabilities—specifically our Process Intelligence Graph—to turn data insights into immediate business action. We believe there is a massive opportunity to unlock global productivity and sustainability by placing intelligence at the core of every business process. Join our mission to make processes work for people, companies, and the planet.

Role Description

As a Senior Value Engineering Consultant specializing in the Energy Sector, you are pushing the envelope in solving business-critical problems for our strategic customers across utilities, oil & gas, and renewable energy. You will be working with our most strategic energy clients, understanding their unique objectives—from grid modernization and asset lifecycle management to navigating the energy transition—and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI, and Databricks.

With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands our customers’ complex business realities (bridging IT and OT systems) and enables them to industrialize AI, unlocking real ROI on deployments at scale. You will prototype these solutions, demonstrate their value to Energy Executives, and ensure successful implementation, adoption, and value realization in order to increase the footprint of Celonis across the global energy landscape.

Key Responsibilities:

AI Discovery & Solutioning: Understand energy customers' AI strategy and sector-specific challenges (e.g., predictive maintenance, outage management, supply chain resilience, or regulatory compliance). As a Celonis product and energy domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle.
Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the pre-sales cycle, and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds are successfully reached.
Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude, and don’t shy away from complex operational problems. Leverage cutting-edge AI technologies to rapidly build creative prototypes in customer hackathons, solving critical pain points specific to power generation, transmission, and O&G operations.
Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale, enabling a fundamental shift from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform (e.g., intelligent field service routing or autonomous procurement).
Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. This includes architecting and delivering secure, scalable LLM/agent systems with RAG, tools, and guardrails, while seamlessly integrating with enterprise data, identity protocols, and stringent energy compliance frameworks.
Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for the Energy vertical, scaling knowledge across the organization regarding utilities, upstream/downstream oil & gas, and renewable energy processes.

Requirements:

5+ years of experience leading technical pre-sales and post-sales engagements specifically within the Energy sector (Utilities, Oil & Gas, and/or Renewables). This includes defining AI roadmaps, building compelling ROI/TCO business cases, and guiding technical implementations through to value realization.
Deep understanding of business processes native to the Energy sector (such as Asset Management, Field Services, Supply Chain, Capital Projects, or Trading) with the ability to translate high-level business needs into specific, impactful AI use cases.
Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases (e.g., automated processing of engineering documents, regulatory filings, or intelligent diagnostic chatbots).
Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies relevant to handling large-scale industrial data.
Strong presentation skills to both internal and external stakeholders (including C-level executives and operational leaders), whether leading technical whiteboarding sessions or formal readouts and demos.
Bachelor’s Degree required; Master's Degree in computer science, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to have (big plus):

Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails suited for highly regulated industries.
Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex) and familiarity with IT/OT convergence and industrial IoT data structures.

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

The base salary range below is for the role in the specified location, based on a Full Time Schedule.

Total compensation package will include base salary + bonus/commission + equity + benefits (health, dental, life, 401k, and paid time off). Please note that the base salary range is a guideline, and that the actual total compensation offer will be determined based on various factors, including, but not limited to, applicant's qualifications, skills, experiences, and location.

The base salary range below is for the role in New York, based on a Full Time Schedule.

$131,000—$154,000 USD

What Celonis can offer you:

Pioneer Innovation: Work with the global leader in Process Mining and the Process Intelligence Graph to shape the future of AI-driven business operations.
Ownership from Day 1: Every full-time "Celonaut" is an owner, receiving Restricted Stock Units (RSUs) and merit-based refresh grants.
Unrivaled Family Support: Benefit from our inclusive parental leave policy—24 weeks of fully paid leave for primary carers and 12 weeks for supporting carers, available from your first day of employment.
Work-Life Integration: Enjoy Unlimited PTO (in applicable regions) and generous PTO globally, as well as a flexible hybrid work model that balances remote focus with vibrant office collaboration.
Continuous Growth: Elevate your skills through our 70-20-10 learning framework, mentorship programs, and access to a dedicated learning platform.
Holistic Well-being: Prioritize your health with subsidized Wellhub memberships, mental health counseling, and dedicated "Wellness Weeks" that prioritize work/life balance.
Drive Sustainability: Participate in annual Impact Days, where you receive paid time off to volunteer for community and environmental causes with your local office, or virtually.
Global Inclusion & Belonging: Find community through our Inclusion Think Tank and participate in our annual Inclusion Days, ensuring every voice is heard and valued.
Value-Driven Impact: Join a mission-led organization where our core values—Live for Customer Value, The Best Team Wins, We Own It, and Earth Is Our Future—drive every decision.

About Us:

Celonis makes processes work — for people, companies, and the planet. Powered by process mining and AI, the Celonis Process Intelligence Platform integrates process data and business context to create a living digital twin of business operations. We enable thousands of companies worldwide to understand how their business actually runs and, together with their partners, build intelligent solutions that transform and continuously improve the way they operate — unlocking billions in value. Celonis is headquartered in Munich, Germany, and New York City, USA, with more than 20 offices worldwide.

Get familiar with the Celonis Process Intelligence Platform by watching this video.

Celonis Inclusion Statement:

At Celonis, we believe our people make us who we are and that “The Best Team Wins”. We know that the best teams are made up of people who bring different perspectives to the table. And when everyone feels included, able to speak up and knows their voice is heard - that's when creativity and innovation happen.

Your Privacy:

Any information you submit to Celonis as part of your application will be processed in accordance with Celonis’ Accessibility and Candidate Notices

By submitting this application, you confirm that you agree to the storing and processing of your personal data by Celonis as described in our Privacy Notice for the Application and Hiring Process.

Please be aware of common job offer scams, impersonators and frauds. Learn more here.

Ready to apply?

Celonis

View all jobs →

Senior Value Engineer -Consumer Goods

Celonis · New York, US, New York

Apply now

Value Engineering New York, US, New York Posted May 8, 2026

Celonis is the global leader in Process Intelligence and the pioneer of Process Mining technology. As one of the world’s fastest-growing enterprise SaaS companies, we are changemakers pushing the boundaries of what’s possible. We invest heavily in advanced AI capabilities—specifically our Process Intelligence Graph—to turn data insights into immediate business action. We believe there is a massive opportunity to unlock global productivity and sustainability by placing intelligence at the core of every business process. Join our mission to make processes work for people, companies, and the planet.

Role Description

As an Senior Value Engineer specializing in CPG and Fleet Logistics, you are pushing the envelope in solving business-critical problems for some of the world's most recognized consumer brands and global mobility networks. You will be working intimately with our most strategic enterprise clients, understanding their uniquely complex objectives—spanning from high-velocity beverage manufacturing and Direct Store Delivery (DSD) optimization to massive-scale fleet lifecycle management and dynamic asset routing. You will build Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with top AI and ML technology partners (e.g., Microsoft, OpenAI, Databricks).

With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands the intricate realities of our customers' massive supply chains, vehicle fleets, and distribution networks. This enables them to industrialize AI, unlocking real ROI on deployments at scale—ensuring products are always on the shelf and vehicles are always ready for the customer. There is no AI without PI. You will prototype these solutions, demonstrate their value to global Chief Supply Chain Officers (CSCOs) and Fleet Operations Executives, and ensure successful implementation, adoption, and value realization to solidify and expand the footprint of Celonis across these premier global networks.

Key Responsibilities:

AI Discovery & Solutioning: Understand the clients' overarching AI strategies and the distinct supply chain challenges inherent to high-volume CPG and fleet mobility (e.g., predictive demand forecasting, route optimization, fleet predictive maintenance, dynamic asset allocation, and mitigating raw material volatility). As a Celonis product and logistics domain expert, translate these complex, physical-world challenges into innovative AI solutions that drive measurable impact.
Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the expansion/pre-sales cycle within various manufacturing, distribution, and fleet management business units. Remain deeply involved post-sale to guide implementation, ensuring agreed value, efficiency, and adoption thresholds are successfully reached.
Hackathons & Prototyping: Think out of the box with a "can-do" attitude, tackling heavily siloed legacy logistics and telematics networks. Leverage cutting-edge AI technologies to rapidly build creative prototypes in client hackathons, solving critical pain points across inventory allocation, fleet routing, and DSD execution.
Agentic Process Transformation: Support these enterprise clients in achieving tangible ROI from AI at scale. Enable a fundamental shift from traditional, rule-based automation to autonomous AI agents empowered by the Celonis Process Intelligence Platform (e.g., autonomous fleet rebalancing, intelligent shipment exception handling, or automated trade promotion deductions).
Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. Architect and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails, ensuring seamless integration with complex enterprise ERPs (e.g., SAP), Transportation Management Systems (TMS), Warehouse Management Systems (WMS), and massive IoT/telematics data streams.
Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for CPG and Mobility Supply Chains, scaling knowledge across the organization regarding the nuances of fast-moving consumer goods and asset-heavy fleet operations.

Requirements:

5+ years of experience leading technical pre-sales and post-sales engagements specifically within highly complex Supply Chain, CPG/Beverage, or Fleet Logistics environments. This includes defining AI roadmaps, building compelling ROI/TCO business cases for large-scale distribution networks, and guiding technical implementations through to value realization.
Deep understanding of supply chain business processes native to high-volume manufacturing and mobility (such as Direct Store Delivery (DSD), Order-to-Cash, Procure-to-Pay, Fleet Lifecycle Management, or Sales & Operations Planning) with the ability to translate high-level operational needs into specific AI use cases.
Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases (e.g., intelligent dispatch assistants, or automated extraction of data from complex vendor contracts and logistics documentation).
Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies for handling massive, high-velocity transactional and IoT datasets.
Strong presentation skills to both internal and external stakeholders (including supply chain executives, logistics directors, and enterprise IT leaders), whether leading technical whiteboarding sessions or formal readouts and demos.
Bachelor’s Degree required; Master's Degree in computer science, supply chain management, logistics, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to have (big plus):

Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations suited for enterprise-grade supply chain environments.
Familiarity with CPG and fleet-specific systems (e.g., SAP APO/IBP, Blue Yonder, Manhattan, or major telematics/fleet tracking platforms).
Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex).

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

The base salary range below is for the role in the specified location, based on a Full Time Schedule.

Total compensation package will include base salary + bonus/commission + equity + benefits (health, dental, life, 401k, and paid time off). Please note that the base salary range is a guideline, and that the actual total compensation offer will be determined based on various factors, including, but not limited to, applicant's qualifications, skills, experiences, and location.

The base salary range below is for the role in New York, based on a Full Time Schedule.

$131,000—$154,000 USD

What Celonis can offer you:

Pioneer Innovation: Work with the global leader in Process Mining and the Process Intelligence Graph to shape the future of AI-driven business operations.
Ownership from Day 1: Every full-time "Celonaut" is an owner, receiving Restricted Stock Units (RSUs) and merit-based refresh grants.
Unrivaled Family Support: Benefit from our inclusive parental leave policy—24 weeks of fully paid leave for primary carers and 12 weeks for supporting carers, available from your first day of employment.
Work-Life Integration: Enjoy Unlimited PTO (in applicable regions) and generous PTO globally, as well as a flexible hybrid work model that balances remote focus with vibrant office collaboration.
Continuous Growth: Elevate your skills through our 70-20-10 learning framework, mentorship programs, and access to a dedicated learning platform.
Holistic Well-being: Prioritize your health with subsidized Wellhub memberships, mental health counseling, and dedicated "Wellness Weeks" that prioritize work/life balance.
Drive Sustainability: Participate in annual Impact Days, where you receive paid time off to volunteer for community and environmental causes with your local office, or virtually.
Global Inclusion & Belonging: Find community through our Inclusion Think Tank and participate in our annual Inclusion Days, ensuring every voice is heard and valued.
Value-Driven Impact: Join a mission-led organization where our core values—Live for Customer Value, The Best Team Wins, We Own It, and Earth Is Our Future—drive every decision.

About Us:

Celonis makes processes work — for people, companies, and the planet. Powered by process mining and AI, the Celonis Process Intelligence Platform integrates process data and business context to create a living digital twin of business operations. We enable thousands of companies worldwide to understand how their business actually runs and, together with their partners, build intelligent solutions that transform and continuously improve the way they operate — unlocking billions in value. Celonis is headquartered in Munich, Germany, and New York City, USA, with more than 20 offices worldwide.

Get familiar with the Celonis Process Intelligence Platform by watching this video.

Celonis Inclusion Statement:

At Celonis, we believe our people make us who we are and that “The Best Team Wins”. We know that the best teams are made up of people who bring different perspectives to the table. And when everyone feels included, able to speak up and knows their voice is heard - that's when creativity and innovation happen.

Your Privacy:

Any information you submit to Celonis as part of your application will be processed in accordance with Celonis’ Accessibility and Candidate Notices

By submitting this application, you confirm that you agree to the storing and processing of your personal data by Celonis as described in our Privacy Notice for the Application and Hiring Process.

Please be aware of common job offer scams, impersonators and frauds. Learn more here.

Ready to apply?

Celonis

View all jobs →

Applied Value Engineer

Celonis · Redwood City, US, California

Apply now

Value Engineering New York, US, New York Redwood City, US, California Posted May 8, 2026

Celonis is the global leader in Process Intelligence and the pioneer of Process Mining technology. As one of the world’s fastest-growing enterprise SaaS companies, we are changemakers pushing the boundaries of what’s possible. We invest heavily in advanced AI capabilities—specifically our Process Intelligence Graph—to turn data insights into immediate business action. We believe there is a massive opportunity to unlock global productivity and sustainability by placing intelligence at the core of every business process. Join our mission to make processes work for people, companies, and the planet.

Role Description

As an Applied AI Engineer you are pushing the envelope in solving business-critical problems for our customers. You will be working with our most strategic customers, understanding their objectives and key challenges, and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

Key Responsibilities:

AI Discovery & Solutioning: Understand customers AI strategy and business critical challenges. As Celonis product & domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle
Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude and don’t shy away from complex problems. Leverage cutting edge AI technologies to rapidly build creative prototypes in customer hackathons solving business critical problems
Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale enabling a fundamental shift in business operations from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform
Proof projects: End-to-end execution of business-critical Proof-of-Value projects, incl. architecture and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks.
Ensure Successful Project Outcome: Applied AI Engineers stay involved with projects until agreed value & adoption thresholds are reached
Specialize in Domains or Industries: To scale knowledge across the organization Applied AI Engineers specialize in domains (e.g. supply chain) and industries

Requirements:

7+ years of experience leading technical pre-sales, including defining AI roadmaps, building compelling ROI/TCO business cases and prototyping of machine learning and generative AI solutions.
Understanding of generative AI techniques like RAG, few shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning that are used to build high-impact use cases like intelligent chatbots and automated text processors.
Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
Good knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.
Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience preferred.

Nice to have (big plus):

Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.
Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex)

The base salary range below is for the role in the specified location, based on a Full Time Schedule.

Total compensation package will include base salary + bonus/commission + equity + benefits (health, dental, life, 401k, and paid time off). Please note that the base salary range is a guideline, and that the actual total compensation offer will be determined based on various factors, including, but not limited to, applicant's qualifications, skills, experiences, and location.

The base salary range below is for the role in California, based on a Full Time Schedule.

$161,250—$191,250 USD

What Celonis can offer you:

Pioneer Innovation: Work with the global leader in Process Mining and the Process Intelligence Graph to shape the future of AI-driven business operations.
Ownership from Day 1: Every full-time "Celonaut" is an owner, receiving Restricted Stock Units (RSUs) and merit-based refresh grants.
Unrivaled Family Support: Benefit from our inclusive parental leave policy—24 weeks of fully paid leave for primary carers and 12 weeks for supporting carers, available from your first day of employment.
Work-Life Integration: Enjoy Unlimited PTO (in applicable regions) and generous PTO globally, as well as a flexible hybrid work model that balances remote focus with vibrant office collaboration.
Continuous Growth: Elevate your skills through our 70-20-10 learning framework, mentorship programs, and access to a dedicated learning platform.
Holistic Well-being: Prioritize your health with subsidized Wellhub memberships, mental health counseling, and dedicated "Wellness Weeks" that prioritize work/life balance.
Drive Sustainability: Participate in annual Impact Days, where you receive paid time off to volunteer for community and environmental causes with your local office, or virtually.
Global Inclusion & Belonging: Find community through our Inclusion Think Tank and participate in our annual Inclusion Days, ensuring every voice is heard and valued.
Value-Driven Impact: Join a mission-led organization where our core values—Live for Customer Value, The Best Team Wins, We Own It, and Earth Is Our Future—drive every decision.

About Us:

Celonis makes processes work — for people, companies, and the planet. Powered by process mining and AI, the Celonis Process Intelligence Platform integrates process data and business context to create a living digital twin of business operations. We enable thousands of companies worldwide to understand how their business actually runs and, together with their partners, build intelligent solutions that transform and continuously improve the way they operate — unlocking billions in value. Celonis is headquartered in Munich, Germany, and New York City, USA, with more than 20 offices worldwide.

Get familiar with the Celonis Process Intelligence Platform by watching this video.

Celonis Inclusion Statement:

At Celonis, we believe our people make us who we are and that “The Best Team Wins”. We know that the best teams are made up of people who bring different perspectives to the table. And when everyone feels included, able to speak up and knows their voice is heard - that's when creativity and innovation happen.

Your Privacy:

Any information you submit to Celonis as part of your application will be processed in accordance with Celonis’ Accessibility and Candidate Notices

By submitting this application, you confirm that you agree to the storing and processing of your personal data by Celonis as described in our Privacy Notice for the Application and Hiring Process.

Please be aware of common job offer scams, impersonators and frauds. Learn more here.

Ready to apply?

Celonis

View all jobs →

Not seeing the right opportunity right now?

Lightning AI · London, England, United Kingdom; New York, New York, United States; Remote; San Francisco, California, United States; Seattle, Washington, United States

Apply now

Posted May 8, 2026

Who We Are

Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.

Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.

We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.

Our Values

Move Fast: We act with speed and precision, breaking down big challenges into achievable steps.
Focus: We complete one goal at a time with care, collaborating as a team to deliver features with precision.
Balance: Sustained performance comes from rest and recovery. We ensure a healthy work-life balance to keep you at your best.
Craftsmanship: Innovation through excellence. Every detail matters, and we take pride in mastering our craft.
Minimal: Simplicity drives our innovation. We eliminate complexity through discipline and focus on what truly matters.

Join our Talent Community!

We’re always looking to connect with exceptional talent. If what we’re building resonates with you, we’d love to learn more about your background and what you’re looking to do next.

If you’d like to be considered for future opportunities with us, please submit your information below. This is an expression of interest, so while we may not be in touch immediately, your information will be kept on file and reviewed as new roles open up. In the meantime, we encourage you to follow us on LinkedIn and check our careers page for updates.

We are hiring across our U.S. and London hubs, and occasionally have remote opportunities as well. If you see a role that aligns with your experience, we recommend applying directly to that posting so our team can review your application as soon as possible.

Benefits and Perks

We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success. Benefits may vary by location, team, and role.

Benefits include:

Comprehensive medical, dental and vision coverage (U.S.); Private medical and dental insurance (U.K.)
Retirement and financial wellness support (U.S.); Pension contribution (U.K.)
Generous paid time off, plus holidays
Paid parental leave
Professional development support
Wellness and work-from-home stipends
Flexible work environment

At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.

Ready to apply?

Lightning AI

View all jobs →

Senior Principal Machine Learning Engineer

SoundCloud · New York

Apply now

Engineering & Infrastructure New York Posted May 8, 2026

SoundCloud empowers artists and fans to connect and share through music. Founded in 2007, SoundCloud is an artist-first platform empowering artists to build and grow their careers by providing them with the most progressive tools, services, and resources. With over 400+ million tracks from 40 million artists, the future of music is SoundCloud.

SoundCloud is seeking a Machine Learning leader to architect the next era of Musical Intelligence at SoundCloud. As a Senior Principal Engineer, you will combine deep technical expertise with strategic vision and people leadership to drive the development of large-scale recommendation, personalization, and search systems. The mission is clear: architect systems to extract high-fidelity insights from user interactions with the world’s largest audio dataset to connect artists and fans through music. You will define the technical North Star for ML across engineering, delivering impactful data-driven products while leading and growing a high-performing team of Engineers and Scientists. This role reports directly to the Chief Technology Officer and will work in lockstep with the Music Intelligence, Content, and Recommendations teams. You will also be part of a small group leading the charge in architecting the agentic workflows and LLM-assisted systems that will allow us to ship Musical Intelligence at 10x the speed of traditional teams.

Key Responsibilities:

Lead the technical strategy and execution for SoundCloud’s ML systems (e.g., recommendation, ranking, personalization), including model development, deployment, and scaling
Lead the exploration of advanced modeling techniques including Deep Neural Networks, LLMs, large recommender systems, multi-modal embeddings and transformer-based architectures to create unique and impactful listening experiences
Define and drive the overall technical direction for ML in SoundCloud including model architecture, feature engineering, training and serving infrastructure at scale, feature stores, pipeline orchestration, and model registry and versioning all aimed at accelerating our ability to bring ML-powered features to market
Own short- and long-term objectives, ensuring ML investments deliver measurable user and business impact
Lead, mentor, and grow ML Engineers and Scientists across SoundCloud
Be a strategic partner to the CTO in bringing an “ML Everywhere” strategy to all surfaces in the product (both Creator and Fan), and helping to lead the charge on AI-native engineering
Stay current with industry trends and advancements in machine learning, identifying opportunities to apply them at SoundCloud
Lead the leveraging of agentic workflows and AI-assisted engineering as a force multiplier to work at 10x the speed of traditional methods

Experience and Background:

10+ years of experience in ML engineering, plus 3+ years in search or recommendations in an internet scale service with the reach of tens of millions of daily active users. Experience in a music streaming environment is a bonus
Proven track record of defining technical strategy and driving execution for large-scale ML systems, particularly in recommendation, personalization, or search
Experience setting technical roadmaps, influencing cross-functional priorities, and balancing business, product, and engineering trade-offs at an organizational level
Experience leading and scaling teams of ML Engineers and Scientists, including hiring, mentoring, and developing high-performing talent
Deep expertise in delivering data-driven products and ML solutions at scale on cloud-based platforms, with strong understanding of infrastructure and lifecycle management
Hands-on familiarity with modern ML frameworks (PyTorch, TensorFlow) and data processing pipelines, combined with strong software engineering foundations
Thought leadership in ML and data science, with a track record of driving technical innovation and applying emerging industry trends
Exceptional communication, strategic influence, and cross-functional leadership skills across senior stakeholders and global teams

The salary range for this role is $280,000 - $325,000 annually. The final salary offered will be determined based on relative experience, skills, internal equity, and location. We also offer a generous total rewards program - read more about additional benefits and perks below!

About us:

We are a multinational company with offices in the US (New York and Los Angeles), Germany (Berlin), and the UK (London)
We provide a flexible work culture that offers the opportunity to collaborate and connect in person at our offices as well as accommodating work from home
We are deeply committed to ensuring diversity, equity and inclusion at all levels of our organization and fostering a community where everyone’s voice, perspective and experience is respected and heard
We believe a strong team is made by investing in employees through mentorship, workshops and enrichment opportunities

Benefits:

Comprehensive health benefits including medical, dental, and vision plans, as well as mental health resources
Robust 401k program
Employee Equity Plan
Generous professional development allowance
Interested in a gym membership, photography course or book? We have a Creativity and Wellness benefit!
Flexible vacation and public holiday policy where you can take up to 35 days of PTO annually
16 paid weeks for all parents (birthing and non-birthing), regardless of gender, to welcome newborns, adopted and foster children
Various snacks, goodies, and 2 free lunches weekly when at the office

Diversity, Equity and Inclusion at SoundCloud

SoundCloud is for everyone. Diversity and open expression are fundamental to our organization; they help us lead what’s next in music by understanding and empowering our creators and fans, no matter their identity. We acknowledge the challenges in the music industry, and strive to influence an inclusive culture where everyone can contribute respectfully and thrive, especially the historically marginalized communities that many of our creators, fans and SoundClouders identify with. We are dedicated to creating an inclusive environment at SoundCloud for everyone, regardless of gender identity, sexual orientation, race, ethnicity, migration background, national origin, age, disability status, or care-giver status.

At SoundCloud you can find your community or elevate your allyship by joining a Diversity Resource Group. Diversity Resource Groups are employee-organized groups focused on supporting and promoting the interests of a particular underrepresented community in order to build a more inclusive culture at SoundCloud. Anyone can join, whether you share the identity or strive to be an ally.

Ready to apply?

Apply to SoundCloud

SoundCloud

View all jobs →

TO

Research Engineer, Frontier Speculative Decoding

Together AI · San Francisco, New York City

Apply now

Research San Francisco Posted May 7, 2026

About the Role

Together AI is building the Inference Platform that powers the world's most advanced generative AI models. Your role will be a critical bridge between cutting-edge research and real-world applications, focusing on making translating our internal model training research to production-ready deployment for our customers. This involves a deep commitment to data-centric development, meticulous hyperparameter tuning, and rigorous checkpoint evaluation before models ever hit production.

This role will involve understanding customer specific needs and fine-tuning models on our internal data recipe and their proprietary data. The goal is to transform general-purpose models into highly performant, specialized tools that solve real business problems. You will not be training foundation models from scratch but rather focusing on creating highly efficient, specialized models by working with dedicated GPU clusters.

Responsibilities

Design and iterate on novel speculator algorithms, combining architectural innovations with carefully curated data to push the frontier of accuracy–efficiency tradeoffs.
Be the critical link between raw data and a production-ready model, seeing your work directly impact our customers' success.
Work in a fast-paced, high-impact role at the cutting edge of generative AI.
Collaborate with a team of experts dedicated to solving real-world, high-performance challenges.
You'll collaborate directly with customers to understand their needs, and work closely with our core inference and Applied ML research teams to integrate your work into the production platform.
A culture of deep technical ownership where you are empowered to take on and solve challenging problems

Requirements

A genuine love for data curation and processing, with a meticulous attention to detail. You believe that great models start with great data.
Demonstrated ability to perform effective hyperparameter searches and understand the trade-offs involved in tuning models for specific tasks.
Experience working with and building on top of existing training codebases. You are comfortable navigating complex code and contributing to its improvement.
Strong attention-to-detail in evaluating model checkpoints to ensure they meet strict quality, performance, and reliability standards.
Experience with Python and PyTorch.
Familiarity with SLURM and/or Kubernetes clusters and experience submitting and managing jobs in a high-performance computing environment.
Familiarity with modern LLMs and generative models.
Basic understanding of distributed training frameworks (e.g., FSDP, DeepSpeed).
Bachelor’s, Master’s degree, or Ph.D. in Computer Science, Computer Engineering, or a related field, or equivalent practical experience.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, ATLAS, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $190,000 - $270,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy

Ready to apply?

Apply to Together AI

TO

Together AI

View all jobs →

Legal Counsel

Lightning AI · New York, New York, United States; San Francisco, California, United States

Apply now

People & Operations New York, New York San Francisco, California Posted May 7, 2026

Who We Are

Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.

Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.

We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.

Our Values

Move Fast: We act with speed and precision, breaking down big challenges into achievable steps.
Focus: We complete one goal at a time with care, collaborating as a team to deliver features with precision.
Balance: Sustained performance comes from rest and recovery. We ensure a healthy work-life balance to keep you at your best.
Craftsmanship: Innovation through excellence. Every detail matters, and we take pride in mastering our craft.
Minimal: Simplicity drives our innovation. We eliminate complexity through discipline and focus on what truly matters.

What We're Looking For

As we continue to expand our footprint, we are looking for a sharp, agile, and business-minded lawyer to join our lean legal team. You will be the primary engine behind our commercial contracting process. This is not a "siloed" role; you will be the cross-functional glue between Finance, Engineering, Sales, and Security, ensuring our legal strategy moves at the speed of our innovation.

This is an ideal opportunity for a high-performing lawyer with a strong grasp of transactional fundamentals who is ready to "level up." While your primary focus will be owning the commercial contract lifecycle, you will have a front-row seat to the broader legal challenges of a hyper-growth AI company.

You will be joining the Legal Team and report to our VP of Legal. This is a hybrid role based in our San Francisco or New York office with an in-office requirement of 2 days per week.

What You’ll Do

Lead the drafting and negotiation of a wide variety of contracts, including Master Service Agreements (MSAs), NDAs, Data Processing Addenda (DPAs), and vendor agreements.
Serve as the legal point of contact for CX, Sales, Engineering, and Finance teams to streamline deal cycles and mitigate risk.
Navigate complex technology transactions, specifically focusing on intellectual property rights and data privacy frameworks in the context of AI and cloud computing.
Beyond commercial matters, you will assist the VP of Legal on special projects, potentially spanning corporate governance, employment, and regulatory compliance as the company scales.

What You’ll Need

3–5 years of legal practice, with a focus on commercial or corporate transactions.
A proven track record at a top-tier law firm, in-house at a high-growth tech company, or a strategic mix of both.
A deep understanding of technology transactions, including the nuances of IP licensing and data privacy provisions.
You are a confident negotiator who knows when to hold the line and when to find a creative solution to get the deal done.

Compensation

We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits.

The anticipated annual base salary range for this role is:

$180,000—$220,000 USD

Benefits and Perks

We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success. Benefits may vary by location, team, and role.

Benefits include:

Comprehensive medical, dental and vision coverage (U.S.); Private medical and dental insurance (U.K.)
Retirement and financial wellness support (U.S.); Pension contribution (U.K.)
Generous paid time off, plus holidays
Paid parental leave
Professional development support
Wellness and work-from-home stipends
Flexible work environment

At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.

Ready to apply?

Lightning AI

View all jobs →

Senior Finance Associate

Lightning AI · New York, New York, United States; San Francisco, California, United States

Apply now

People & Operations New York, New York San Francisco, California Posted May 7, 2026

Who We Are

Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.

Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.

We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.

Our Values

Move Fast: We act with speed and precision, breaking down big challenges into achievable steps.
Focus: We complete one goal at a time with care, collaborating as a team to deliver features with precision.
Balance: Sustained performance comes from rest and recovery. We ensure a healthy work-life balance to keep you at your best.
Craftsmanship: Innovation through excellence. Every detail matters, and we take pride in mastering our craft.
Minimal: Simplicity drives our innovation. We eliminate complexity through discipline and focus on what truly matters.

What We’re Looking For

We are looking for a Senior Finance Associate to drive priorities across strategic finance, corporate development, and FP&A as Lightning AI scales. You will partner with cross-functional stakeholders to shape unit economics, advise on deal pricing, and guide investment decisions. You will support GPU financing, fundraising, and investor relations to help Lightning AI acquire and allocate capital effectively. You will also build an operating cadence for P&L management, reporting, forecasting, and planning, turning data into decision-ready insights for leadership.

The finance scope is deep, leadership visibility is high, and the work directly influences revenue growth, margin expansion, and capital allocation. If you want meaningful ownership, steep learning, and proximity to the decisions that shape an AI cloud, this role is for you.

This is a hybrid role based in our San Francisco or New York office with an in-office requirement of 2 days per week.

What You’ll Do

Support deal reviews with Sales and leadership and recommend pricing decisions
Partner with Marketing on spend allocation, pipeline efficiency, and unit economics analyses (LTV/CAC, payback period)
Partner with Product on ROI for software investments and strategic initiatives
Partner with Infrastructure Operations on capacity planning and CapEx assessment
Model GPU financing structures and assess returns
Support lender and investor communications, materials, and data rooms
Monitor industry trends and the competitive landscape to identify potential business risks and opportunities
Contribute to M&A sourcing and diligence models
Build and maintain a driver based model for P&L, balance sheet, and cash flow statement
Prepare executive-level business reviews for leadership and board
Lead monthly and quarterly reporting, ensuring accuracy and highlighting key business drivers
Develop forecast cycles and strengthen forecast accuracy by partnering closely with cross-functional stakeholders
Support annual planning and long-range planning
Conduct rigorous analysis of key performance indicators, operational metrics, and business trends
Manage FP&A systems and tooling and maintain data accuracy

What You’ll Need

Bachelor's degree in Business Administration, Finance, Economics, or a related field
4+ years in Strategic Finance, FP&A, investment banking, private equity, or venture capital, ideally with a focus on software, AI, and/or cloud infrastructure
Advanced proficiency in Excel and Google Sheets and experience building complex financial models
Excellent written and verbal communication
Track record of cross-functional partnership
Analytical and strong problem-solving ability
Team player with a growth mindset, positive attitude, and strong work ethic
Bias to action and desire to work in a startup environment
Experience with capital markets, M&A, or CapEx financing
Exposure to cloud or AI infrastructure economics and data center capacity planning
Familiarity with FP&A systems and data tooling (e.g., NetSuite)

Compensation

We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits.

The anticipated annual base salary range for this role is:

$135,000—$165,000 USD

Benefits and Perks

We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success. Benefits may vary by location, team, and role.

Benefits include:

Comprehensive medical, dental and vision coverage (U.S.); Private medical and dental insurance (U.K.)
Retirement and financial wellness support (U.S.); Pension contribution (U.K.)
Generous paid time off, plus holidays
Paid parental leave
Professional development support
Wellness and work-from-home stipends
Flexible work environment

At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.

Ready to apply?

Lightning AI

View all jobs →

Machine Learning Solutions Engineer (ML + Infrastructure Focus)

Lightning AI · New York, New York, United States

Apply now

Sales New York, New York San Francisco, California Posted May 7, 2026

Who We Are

Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.

Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.

We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.

Our Values

Move Fast: We act with speed and precision, breaking down big challenges into achievable steps.
Focus: We complete one goal at a time with care, collaborating as a team to deliver features with precision.
Balance: Sustained performance comes from rest and recovery. We ensure a healthy work-life balance to keep you at your best.
Craftsmanship: Innovation through excellence. Every detail matters, and we take pride in mastering our craft.
Minimal: Simplicity drives our innovation. We eliminate complexity through discipline and focus on what truly matters.

What We're Looking For

As a Machine Learning Solutions Engineer, you will operate at the intersection of machine learning, distributed systems, and cloud infrastructure.
You will partner with customers to design and deploy end-to-end AI systems, spanning:

Model development and training
GPU infrastructure and cluster design
Distributed inference and production deployment

This role goes beyond traditional ML solutions engineering—you will act as a technical architect, helping customers make critical decisions across compute, orchestration, and system design.

The role can be based out of our New York City or San Francisco office, with an in-office requirement of at least 2-3 days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this role at this time. The annual base pay range for this role is $150,000 - $195,000, in addition to a variable pay component and meaningful equity.

What You’ll Do

Customer Architecture & Technical Leadership

Partner with customers to understand ML workloads, infrastructure constraints, and scaling requirements
Architect end-to-end solutions across:

Data pipelines (CPU → GPU workflows)
Distributed training (multi-node, multi-GPU)
High-throughput inference systems

Translate business goals (latency, cost, throughput) into technical system design decisions

GPU & Infrastructure Design

Design and optimize workloads across GPU clusters (H100, H200, B200, etc.)
Advise on:

Training vs inference cluster design
Interconnect choices (Ethernet vs Infiniband / RDMA vs Roce)
Storage strategies (local NVMe vs networked / object storage)

Model and optimize for:

Tokens/sec, tokens/$
Throughput vs latency tradeoffs
GPU utilization and scheduling efficiency

Kubernetes & Platform Systems

Design and support deployments on Kubernetes (EKS, GKE, on-prem clusters)
Work with:

GPU scheduling (time-slicing, MIG, bin-packing)
Autoscaling and workload orchestration
Helm-based deployments and multi-tenant environments

Help customers balance:

Raw Kubernetes flexibility vs platform abstraction (Lightning)

Demos, POCs, and Execution

Build and deliver technical demos and POCs that showcase:

Distributed training workflows
Scalable inference endpoints
End-to-end ML pipelines on Lightning AI

Scope and lead POCs aligned to customer success metrics (latency, cost, reliability)

Cross-Functional Impact

Act as the bridge between customers, product, and engineering
Provide feedback on:

Platform gaps in infrastructure, orchestration, and performance
Emerging patterns in GPU usage and distributed systems

Influence roadmap across ML workflows and infrastructure capabilities

Enablement & Thought Leadership

Create technical content
Architecture guides (e.g., high-throughput LLM inference systems)
Best practices for GPU utilization and scaling
Educate customers on modern AI infrastructure patterns

What You’ll Need

ML + Systems Expertise

3–6+ years experience in:

Machine Learning / AI Engineering
Solutions Engineering / Sales Engineering / ML Consulting

Strong understanding of:

Training vs inference workloads
Model optimization (quantization, batching, caching, etc.)

GPU & Distributed Systems

Experience working with:

GPU clusters (NVIDIA stack preferred)
Distributed training or inference systems

Familiarity with:

NCCL, CUDA, or GPU performance profiling
Networking concepts (RDMA, Roce, Infiniband, high-throughput systems)

Kubernetes & Cloud Platforms

Hands-on experience with:

Kubernetes (EKS, GKE, or on-prem)
Slurm
Containerization (Docker)

Exposure to:

GPU scheduling in Kubernetes environments
Multi-tenant or production ML deployments

Programming & Tooling

Strong Python skills (PyTorch preferred)
Experience building:

ML pipelines
APIs or inference services

Familiarity with Lightning AI, PyTorch Lightning, or similar frameworks is a plus

Customer-Facing Excellence

- Ability to:
  - Explain complex infrastructure and ML tradeoffs clearly
  - Run technical discovery and uncover quantifiable success metrics
- Experience working cross-functionally with:
  - Sales, product, and engineering teams

Benefits and Perks

We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success. Benefits may vary by location, team, and role.

Benefits include:

Comprehensive medical, dental and vision coverage (U.S.); Private medical and dental insurance (U.K.)
Retirement and financial wellness support (U.S.); Pension contribution (U.K.)
Generous paid time off, plus holidays
Paid parental leave
Professional development support
Wellness and work-from-home stipends
Flexible work environment

At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.

Ready to apply?

Lightning AI

View all jobs →

Infrastructure Engineer (Storage)

Lightning AI · New York, New York, United States; Remote; San Francisco, California, United States; Seattle, Washington, United States

Apply now

Infrastructure New York, New York San Francisco, California Seattle, WA Remote Posted May 7, 2026

Who We Are

Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.

Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.

We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.

Our Values

Move Fast: We act with speed and precision, breaking down big challenges into achievable steps.
Focus: We complete one goal at a time with care, collaborating as a team to deliver features with precision.
Balance: Sustained performance comes from rest and recovery. We ensure a healthy work-life balance to keep you at your best.
Craftsmanship: Innovation through excellence. Every detail matters, and we take pride in mastering our craft.
Minimal: Simplicity drives our innovation. We eliminate complexity through discipline and focus on what truly matters.

What We're Looking For

Lightning AI is seeking a Senior Storage Infrastructure Engineer to join our Infrastructure Engineering team.

In this role, you will focus on building and operating the storage systems that power large-scale AI/ML training, inference, and HPC workloads. You will work at the intersection of software, hardware, and operations—developing automation, improving reliability, and scaling distributed storage systems across our bare-metal infrastructure.

You will help own the data plane of our storage infrastructure, supporting high-throughput, low-latency data access for some of the most demanding AI workloads. You’ll play a key role in managing and evolving our storage stack (including VAST and S3-compatible systems like Ceph), ensuring performance, reliability, and efficiency at scale.

We’re flexible on location for this team. This role can work hybrid out of one of our US-based hubs (Seattle, NYC, or SF) or fully remote within the U.S., with occasional company and team offsites. We are not able to provide visa sponsorship for this position at this time.

What You'll Do

Storage Systems & Infrastructure

Operate and scale distributed storage systems, including VAST and S3-compatible object storage (e.g., Ceph)
Improve performance, reliability, and efficiency of storage systems supporting large-scale AI/ML workloads
Troubleshoot complex storage and data path issues across hardware and software layers
Optimize storage performance to support high-throughput, low-latency AI training and inference workloads

Automation & Tooling

Build and maintain automation for provisioning, managing, and monitoring storage infrastructure
Develop Python-based tools and workflows to reduce manual operational overhead
Improve lifecycle management of storage clusters, from deployment through maintenance and scaling

Systems & Operations

Manage and operate Linux-based systems in production, including bare-metal environments
Partner with infrastructure and data center teams on hardware bring-up, upgrades, and issue resolution
Support capacity planning, utilization tracking, and forecasting for storage systems
Leverage monitoring and telemetry to diagnose issues and improve system performance and reliability

Cross-Functional Collaboration

Work closely with Infrastructure Engineering, Network Engineering, and Platform teams to integrate storage into the broader platform
Contribute to design discussions around new infrastructure deployments and scaling strategies
Help define best practices for operating storage systems in high-performance computing environments

What You'll Need

Required Qualifications

5+ years of experience in infrastructure engineering, systems engineering, or related roles
Hands-on experience operating distributed storage systems (e.g., VAST, Ceph, or similar)
Strong Linux systems experience in production environments
Proficiency in Python or similar scripting/programming languages for automation
Experience working with bare-metal infrastructure and hardware-oriented systems
Ability to debug complex issues across system boundaries (storage, OS, hardware, networking)
Experience with storage networking protocols (e.g., NFS or similar)
Experience with capacity planning, monitoring, and performance tuning

Ideal Experience

Experience with VAST storage systems in production environments
Experience operating S3-compatible object storage at scale
Data center operations experience, including working with physical hardware
Familiarity with AI/ML or HPC workloads and their storage requirements
Background in high-performance or low-latency distributed systems
Familiarity with high-performance data transfer technologies (e.g., RDMA, GPU Direct Storage)
Experience supporting GPU-based workloads or large-scale compute clusters

Compensation

We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits.

The anticipated annual base salary range for this role is:

$180,000—$200,000 USD

Benefits and Perks

We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success. Benefits may vary by location, team, and role.

Benefits include:

Comprehensive medical, dental and vision coverage (U.S.); Private medical and dental insurance (U.K.)
Retirement and financial wellness support (U.S.); Pension contribution (U.K.)
Generous paid time off, plus holidays
Paid parental leave
Professional development support
Wellness and work-from-home stipends
Flexible work environment

At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.

Ready to apply?

Lightning AI

View all jobs →

Infrastructure Engineer (Observability)

Lightning AI · New York, New York, United States; Remote; San Francisco, California, United States; Seattle, Washington, United States

Apply now

Infrastructure New York, New York San Francisco, California Seattle, WA Remote Posted May 7, 2026

Who We Are

Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.

Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.

We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.

Our Values

Move Fast: We act with speed and precision, breaking down big challenges into achievable steps.
Focus: We complete one goal at a time with care, collaborating as a team to deliver features with precision.
Balance: Sustained performance comes from rest and recovery. We ensure a healthy work-life balance to keep you at your best.
Craftsmanship: Innovation through excellence. Every detail matters, and we take pride in mastering our craft.
Minimal: Simplicity drives our innovation. We eliminate complexity through discipline and focus on what truly matters.

What We’re Looking For

Lightning AI is seeking an Observability Infrastructure Engineer to join our Infrastructure Engineering team.

In this role, you will own and evolve observability systems across large-scale, GPU-enabled bare-metal infrastructure. You’ll operate at the intersection of infrastructure, data, and product, building platforms for metrics, logs, traces, and alerting that power both internal operations and customer-facing visibility.

You will play a key role in productizing observability, enabling scalable, multi-tenant monitoring experiences while keeping pace with rapid infrastructure buildouts. This includes designing telemetry pipelines, improving signal quality, and delivering actionable insights that ensure reliability and transparency across our platform.

We’re flexible on location for this team. This role can work hybrid out of one of our US-based hubs (Seattle, NYC, or SF) or fully remote within the U.S., with occasional company and team offsites. We are not able to provide visa sponsorship for this position at this time.

What You’ll Do

Observability Platform & Productization

Own and evolve a scalable observability platform spanning metrics, logs, traces, and events
Drive the productization of observability capabilities for both internal teams and external customers
Design multi-tenant observability systems with scoped access, RBAC, and customer-facing visibility
Continuously improve observability systems to keep pace with rapid infrastructure buildouts

Telemetry & Data Pipelines

Design and operate telemetry pipelines ingesting data from GPUs, CPUs, networking (Ethernet & InfiniBand), containers, APIs, and BMC/Redfish
Build systems to correlate signals across infrastructure layers to enable faster debugging and root cause analysis
Implement streaming and real-time data pipelines using tools such as Kafka, OTEL, Promtail, or similar

Alerting, Reliability & Insights

Design and implement noise-resistant alerting systems to improve signal quality and reduce operational load
Create dashboards and alerting for InfraOps, Engineering, and Customer Success teams
Build automated insights and enable proactive detection, forecasting, and system health visibility at scale

Systems & Infrastructure Engineering

Contribute to broader infrastructure engineering projects beyond observability
Partner with infrastructure and platform teams to embed observability into core systems and workflows
Support large-scale, distributed systems across compute, networking, and storage environments

Cross-Functional Collaboration

Work closely with customer-facing teams to deliver external observability experiences
Collaborate with engineering, operations, and support teams to improve system transparency and reliability
Help define best practices for observability across the organization

What You’ll Need

Required Qualifications

5+ years of experience in infrastructure engineering, SRE, or observability-focused roles
Strong experience with monitoring systems such as Prometheus, Grafana, ELK, or VictoriaMetrics
Experience building and operating observability platforms at scale
Proficiency in Python, Go, or bash for automation and data integration
Familiarity with containerized environments and Kubernetes observability
Experience with streaming telemetry pipelines (Kafka, OTEL, Promtail, or equivalent)
Experience with multi-tenant monitoring architectures
Strong written and verbal communication skills

Ideal Experience

Experience with GPU observability, particularly NVIDIA DCGM
Experience monitoring large-scale GPU or HPC clusters
Familiarity with InfiniBand fabric observability
Experience building customer-facing or productized infrastructure systems
Experience with correlation engines, RCA workflows, or predictive alerting systems
Broad exposure to infrastructure domains including networking, storage, and provisioning

Compensation

We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits.

The anticipated annual base salary range for this role is:

$180,000—$200,000 USD

Benefits and Perks

We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success. Benefits may vary by location, team, and role.

Benefits include:

Comprehensive medical, dental and vision coverage (U.S.); Private medical and dental insurance (U.K.)
Retirement and financial wellness support (U.S.); Pension contribution (U.K.)
Generous paid time off, plus holidays
Paid parental leave
Professional development support
Wellness and work-from-home stipends
Flexible work environment

At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.

Ready to apply?

Lightning AI

View all jobs →

Machine Learning Engineer, AI

Biohub · New York, NY (Hybrid)

Apply now

AI Research CZ Biohub Network Posted May 7, 2026

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere.

Biohub operates one of the largest AI compute clusters dedicated to biology, spanning three frontier research institutes with some of the world's leading biologists. We're not a startup trying to find product-market fit, and we're not a pharma company optimizing a pipeline. We're building frontier AI for fundamental science, as open science, at a scale no one else is doing. This is a unique moment for scientific acceleration. The problems are among the hardest and most impactful problems you can choose to work on, and we move at a pace that meets this moment.

Our research spans:

Frontier molecular modeling, from protein language models (e.g., ESM) to structure prediction (e.g., ESMFold) and beyond.
Scaled biological foundation models trained on some of the largest GPU clusters dedicated to science
Imaging foundation models trained across the world's largest microscopy datasets
Reasoning and agentic systems that connect frontier LLMs with biological foundation models
Mechanistic interpretability of biological foundation models: extracting new biological knowledge directly from model weights
Scientific data at unprecedented scale: AI systems to collect, curate, and learn from some of the richest biological datasets ever assembled

Join our Team!

As an ML Engineer, you'll join some of the strongest infrastructure engineers in AI, building the systems that connect everything together. The infrastructure problems you solve directly determine what science becomes possible.

What You'll Do

Work with high-dimensional scientific data formats and contribute to backend compatibility, format evaluation, and I/O performance benchmarking at petabyte scale.
Define and shape the engineering patterns your team and collaborating researchers will build on for years; the abstractions you write today become the foundation others depend on at scale.
Work at the intersection of AI systems and biological discovery, where the infrastructure problems you solve directly determine what science becomes possible.
Deploy models to production and manage artifact tracking across models and datasets.
Design and optimize GPU-native data loading pipelines for large-scale multi-dimensional tensor workloads, including profiling and resolving hardware utilization bottlenecks across multi-backend systems.
Work on simplification and improvement of codebase abstractions to accelerate research momentum.
Build and maintain primitives for pre-training infrastructure that ensure the reliability and continuity of large-scale training runs.
Help cultivate best practices in MLOps, and think about the full ML lifecycle, including data, fine-tuning, deployment, reliability and monitoring.
Possesses the ability to execute complex modifications to the research pipeline, such as fast data loading and distributed training.
Handle DevOps responsibilities, focused on making all engineers and researchers more productive. This includes tasks like cluster monitoring, unit testing and integration testing of research codebase, and continuous integration.
Collaborate with partner researchers and engineers to deploy our technology within external infrastructure.

What You'll Bring

Hands-on experience with PyTorch, including custom training loops, distributed training, or low-level performance work.
Familiarity with GPU-native data I/O tools and large-scale tensor formats (e.g. Zarr, HDF5, TensorStore, or similar).
Experience with distributed computing frameworks such as Apache Spark, Dask, or Ray.
Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
Experience building or working with AI agent frameworks is a plus.
A track record of building systems that other engineers and researchers depend on. Not just running experiments, but shipping infrastructure that scales.

Compensation

The future anticipated Redwood City, CA, and New York City, NY base pay range for a role in this field is $150,000 to $350,000+ annually. Compensation ranges will vary based on job-related skills, level of experience, and knowledge. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.

Benefits for the Whole You

We’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible.

Provides a generous employer match on employee 401(k) contributions to support planning for the future.
Paid time off to volunteer at an organization of your choice.
Funding for select family-forming benefits.
Relocation support for employees who need assistance moving

Please note that applying to this opportunity does not guarantee that we will be in touch with you regarding our opportunities. Our recruiting team will contact you if your experience aligns with the skills we seek for future open positions. We will keep your interest on file, contact you as opportunities arise, and send you information about the exciting work we are doing at Biohub. You can opt out at any time!

#LI-Hybrid

Ready to apply?

Apply to Biohub

Biohub

View all jobs →

Infrastructure Engineer (GPU & Compute)

Lightning AI · New York, New York, United States; Remote; San Francisco, California, United States; Seattle, Washington, United States

Apply now

Infrastructure New York, New York San Francisco, California Seattle, WA Remote Posted May 7, 2026

Who We Are

Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.

Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.

We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.

Our Values

Move Fast: We act with speed and precision, breaking down big challenges into achievable steps.
Focus: We complete one goal at a time with care, collaborating as a team to deliver features with precision.
Balance: Sustained performance comes from rest and recovery. We ensure a healthy work-life balance to keep you at your best.
Craftsmanship: Innovation through excellence. Every detail matters, and we take pride in mastering our craft.
Minimal: Simplicity drives our innovation. We eliminate complexity through discipline and focus on what truly matters.

What We're Looking For

Lightning AI is seeking a GPU & Compute Infrastructure Engineer to join our Infrastructure Engineering team.

In this role, you will own image management, system diagnostics, and validation across large-scale bare-metal compute infrastructure, with a particular focus on GPU-enabled systems. You will work at the intersection of hardware, systems, and software—developing automation, improving reliability, and enabling efficient cluster bring-up for AI/ML and HPC workloads.

You will play a key role in owning and evolving our image pipeline, running validation environments and test clusters, and supporting both system-level and GPU hardware qualification. This role is critical to ensuring that our infrastructure is consistent, performant, and ready to support demanding AI workloads from day one.

We’re flexible on location for this team. This role can work hybrid out of one of our US-based hubs (Seattle, NYC, or SF) or fully remote within the U.S., with occasional company and team offsites. We are not able to provide visa sponsorship for this position at this time.

What You'll Do

Systems, Image & Validation Infrastructure

Own and evolve systems for image management, deployment, and validation across bare-metal infrastructure
Run and maintain test clusters used for system validation, diagnostics, and bring-up
Validate firmware, drivers, and OS images across compute and GPU-enabled systems
Support hardware qualification efforts for next-generation platforms

GPU Diagnostics & Performance

Own GPU diagnostics and validation workflows across large-scale infrastructure
Diagnose and resolve complex issues across GPUs, drivers, OS, and hardware layers
Analyze system and GPU performance using tools such as NVIDIA DCGM
Identify failure patterns and drive improvements in system stability and validation coverage

Automation & Tooling

Build and maintain automation for provisioning, validation, and system bring-up
Develop Python-based tools and workflows to improve efficiency and reduce manual operational overhead
Improve the reliability, repeatability, and scalability of image pipelines and validation systems

Systems & Operations

Manage and operate Linux-based systems in production and validation environments
Manage virtualization technology
Support bare-metal provisioning workflows, including PXE and image-based systems
Interface with hardware management systems (e.g., IPMI, Redfish) for monitoring and debugging

Cross-Functional Collaboration

Partner with Infrastructure, Hardware, and Data Center teams on system bring-up and validation
Collaborate with platform and ML teams to ensure systems meet workload requirements
Contribute to best practices for provisioning, diagnostics, and lifecycle management of infrastructure

What You'll Need

Required Qualifications

5+ years of experience in infrastructure engineering, systems engineering, or related roles
Strong Linux systems experience in production environments
Hands-on experience with GPU-enabled systems and tools such as NVIDIA DCGM
Familiarity with bare-metal provisioning and system bring-up workflows
Proficiency in Python or similar scripting/programming languages for automation
Ability to debug complex issues across hardware, OS, GPUs, and system software

Ideal Experience

Experience with high-performance interconnects (e.g., InfiniBand, NVLink)
Experience with PXE boot environments, LiveCD systems, or image-based provisioning workflows
Experience with hardware management interfaces such as iDRAC, IPMI, or Redfish
Data center operations experience, including working with physical hardware
Experience supporting AI/ML or HPC workloads at scale
Experience with GPU validation frameworks or large-scale hardware qualification processes

Compensation

We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits.

The anticipated annual base salary range for this role is:

$180,000—$200,000 USD

Benefits and Perks

We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success. Benefits may vary by location, team, and role.

Benefits include:

Comprehensive medical, dental and vision coverage (U.S.); Private medical and dental insurance (U.K.)
Retirement and financial wellness support (U.S.); Pension contribution (U.K.)
Generous paid time off, plus holidays
Paid parental leave
Professional development support
Wellness and work-from-home stipends
Flexible work environment

At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.

Ready to apply?

Lightning AI

View all jobs →

Fullstack Engineer

Lightning AI · London, England, United Kingdom; New York, New York, United States; San Francisco, California, United States; Seattle, Washington, United States

Apply now

Engineering New York, New York San Francisco, California Seattle, WA London, UK Posted May 7, 2026

Who We Are

Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.

Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.

We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.

Our Values

Move Fast: We act with speed and precision, breaking down big challenges into achievable steps.
Focus: We complete one goal at a time with care, collaborating as a team to deliver features with precision.
Balance: Sustained performance comes from rest and recovery. We ensure a healthy work-life balance to keep you at your best.
Craftsmanship: Innovation through excellence. Every detail matters, and we take pride in mastering our craft.
Minimal: Simplicity drives our innovation. We eliminate complexity through discipline and focus on what truly matters.

What We're Looking For

We’re looking for a Fullstack Engineer to help develop and scale the Lightning AI platform across the frontend, CLI, APIs, and core backend systems. In this role, you’ll take ownership of key features and drive them end-to-end, working closely with engineering, product, and design to ship high-quality, iterative improvements. This is an opportunity to build systems that support real-world machine learning workloads at scale.

This role is based in one of our hubs (NYC, SF, Seattle, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time.

What You’ll Do

Write readable/testable/efficient code in React and either Python or Go (Golang).
Build deep expertise in our technology stack to deliver new features, improve system stability, and increase overall performance.
Partner with engineering and product leaders on developing the Lightning product while using your experience to set the technical direction for large projects.
Evaluate, strengthen, and document technical architecture, tools, and processes.
Maintain high standards for software quality, implement automation, drive continuous delivery, and reduce time to production while proactively reducing technical debt.
Mentor and coach engineers on system design, operating in high uncertainty, and problem-solving to create a supportive, inclusive environment where each engineer can grow.

What You’ll Need

Proficiency in React and either Go (Golang) or Python, with a preference for Go
Strong understanding of software engineering principles and lifecycle
Hands-on experience as a Fullstack Engineer in a SaaS technology company
Proven ability to take ownership of key features and drive end-to-end development
Communication and collaboration with engineers, product managers, and designers
Ability to operate in high uncertainty and rapidly changing environments

Compensation

We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits.

The anticipated annual base salary range for this role is:

$120,000—$250,000 USD

Benefits and Perks

We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success. Benefits may vary by location, team, and role.

Benefits include:

Comprehensive medical, dental and vision coverage (U.S.); Private medical and dental insurance (U.K.)
Retirement and financial wellness support (U.S.); Pension contribution (U.K.)
Generous paid time off, plus holidays
Paid parental leave
Professional development support
Wellness and work-from-home stipends
Flexible work environment

At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.

Ready to apply?

Lightning AI

View all jobs →

Frontend Engineer

Lightning AI · London, England, United Kingdom; New York, New York, United States; San Francisco, California, United States; Seattle, Washington, United States

Apply now

Engineering New York, New York San Francisco, California Seattle, WA Posted May 7, 2026

Who We Are

Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.

Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.

We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.

Our Values

Move Fast: We act with speed and precision, breaking down big challenges into achievable steps.
Focus: We complete one goal at a time with care, collaborating as a team to deliver features with precision.
Balance: Sustained performance comes from rest and recovery. We ensure a healthy work-life balance to keep you at your best.
Craftsmanship: Innovation through excellence. Every detail matters, and we take pride in mastering our craft.
Minimal: Simplicity drives our innovation. We eliminate complexity through discipline and focus on what truly matters.

What We're Looking For

We’re looking for a Frontend Engineer to help develop and scale the UI and frontend infrastructure of the Lightning AI platform. In this role, you’ll take ownership of key features and drive them end-to-end, working closely with engineering, product, and design to ship high-quality, iterative improvements. With over 10,000 organizations building with Lightning, you’ll have a unique opportunity to impact how the world builds and deploys AI to production.

This role is based in one of our hubs (Seattle, NYC, SF, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time.

What You’ll Do

Write readable/testable/efficient code in React and Redux, and build deep expertise in our technology stack to deliver new features, improve system stability, and increase overall performance.
Partner with engineering and product leaders on developing the user interface and frontend infrastructure while using your experience to set the technical direction for large projects.
Evaluate, strengthen, and document technical architecture, tools, and processes.
Maintain high standards for software quality, implement automation, drive continuous delivery, and reduce time to production while proactively reducing technical debt.
Mentor and coach engineers on system design, operating in high uncertainty, and problem-solving to create a supportive, inclusive environment in which each engineer can grow.

What You’ll Need

Proficiency in React, JavaScript and TypeScript.
Strong understanding of software engineering principles and lifecycle.
Hands-on experience as a Frontend Engineer in a SaaS technology company.
Proven ability to take ownership of key features and drive end-to-end development.
Communication and collaboration with engineers, product managers, and designers.
Ability to operate in high uncertainty and rapidly changing environments.

Compensation

We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits.

The anticipated annual base salary range for this role is:

$120,000—$250,000 USD

Benefits and Perks

We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success. Benefits may vary by location, team, and role.

Benefits include:

Comprehensive medical, dental and vision coverage (U.S.); Private medical and dental insurance (U.K.)
Retirement and financial wellness support (U.S.); Pension contribution (U.K.)
Generous paid time off, plus holidays
Paid parental leave
Professional development support
Wellness and work-from-home stipends
Flexible work environment

At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.

Ready to apply?

Lightning AI

View all jobs →

Backend Engineer

Lightning AI · London, England, United Kingdom; New York, New York, United States; San Francisco, California, United States; Seattle, Washington, United States

Apply now

Engineering New York, New York San Francisco, California Seattle, WA Posted May 7, 2026

Who We Are

Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.

Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.

We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.

Our Values

Move Fast: We act with speed and precision, breaking down big challenges into achievable steps.
Focus: We complete one goal at a time with care, collaborating as a team to deliver features with precision.
Balance: Sustained performance comes from rest and recovery. We ensure a healthy work-life balance to keep you at your best.
Craftsmanship: Innovation through excellence. Every detail matters, and we take pride in mastering our craft.
Minimal: Simplicity drives our innovation. We eliminate complexity through discipline and focus on what truly matters.

What We're Looking For

We’re looking for a Backend Engineer to help develop and scale the Lightning AI platform, spanning APIs, infrastructure, billing, security, and integrations. In this role, you’ll take ownership of key features and drive them end-to-end, working closely with engineering, product, and design to ship high-quality, iterative improvements. This is an opportunity to build systems that support real-world machine learning workloads at scale.

This role is based in one of our hubs (Seattle, NYC, SF, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time.

What You’ll Do

Write readable/testable/efficient code in Go (Golang).
Build deep expertise in our technology stack to deliver new features, improve system stability, and increase overall performance.
Partner with engineering and product leaders on developing the Lightning product while using your experience to set the technical direction for large projects.
Evaluate, strengthen, and document technical architecture, tools, and processes.
Maintain software quality, implement automation, drive continuous delivery, and reduce time to production while proactively reducing technical debt.
Mentor and coach engineers on system design, operating in high uncertainty, and problem-solving to create a supportive, inclusive environment where each engineer can grow.

What You’ll Need

Extensive experience writing efficient, maintainable code in Go. Familiarity with best practices in testing, readability, and optimization is essential.
Broad knowledge of backend and frontend systems, with experience building and scaling APIs, CLI tools, billing systems, and security protocols. Exposure to frontend frameworks is a plus.
Experience with cloud platforms like AWS, GCP, or Azure and designing systems that are reliable, performant, and scalable. Familiarity with containerization (Docker, Kubernetes) is a strong advantage.
Proven ability to take ownership of key features and drive end-to-end development
Commitment to software quality, test automation, and continuous delivery. Experience proactively managing technical debt and speeding up time to production.
Hands-on experience as a backend or product engineer in a SaaS technology company
Communication and collaboration with engineers, product managers, and designers
Ability to operate in high uncertainty and rapidly changing environments

Compensation

We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits.

The anticipated annual base salary range for this role is:

$120,000—$250,000 USD

Benefits and Perks

We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success. Benefits may vary by location, team, and role.

Benefits include:

Comprehensive medical, dental and vision coverage (U.S.); Private medical and dental insurance (U.K.)
Retirement and financial wellness support (U.S.); Pension contribution (U.K.)
Generous paid time off, plus holidays
Paid parental leave
Professional development support
Wellness and work-from-home stipends
Flexible work environment

At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.

Ready to apply?

Lightning AI

View all jobs →

Account Executive

Lightning AI · New York, New York, United States

Apply now

Sales New York, New York San Francisco, California Posted May 7, 2026

Who We Are

Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.

Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.

We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.

Our Values

Move Fast: We act with speed and precision, breaking down big challenges into achievable steps.
Focus: We complete one goal at a time with care, collaborating as a team to deliver features with precision.
Balance: Sustained performance comes from rest and recovery. We ensure a healthy work-life balance to keep you at your best.
Craftsmanship: Innovation through excellence. Every detail matters, and we take pride in mastering our craft.
Minimal: Simplicity drives our innovation. We eliminate complexity through discipline and focus on what truly matters.

What We're Looking For

We are looking for an Account Executive with experience selling highly technical, developer-focused products to CTOs, VPs of Engineering, software engineers, researchers, and/or data scientists. You thrive in a fast-paced, start-up environment focusing on every step of the sales process, from prospecting, qualifying, and nurturing leads to running demos, negotiating contracts, and closing deals. We want someone who thinks about how to uncover and address our customers’ problems to drive customer acquisition while feeding their requirements back to inform the product roadmap.

This role is based out of our New York City office, with an in-office requirement of at least 3 days per week and occasional team and company offsites.

What You’ll Do

Build an understanding of our target markets, value proposition, and pricing models to not only meet but exceed quarterly revenue targets.
Focus on high-quality, consistent outbound prospecting across key market segments to build the sales pipeline and optimize the customer funnel.
Qualify and develop both inbound and outbound sales leads.
Collaborate with the product, engineering, and marketing teams to continuously improve and iterate on the sales process.
Analyze industry trends and customer segmentation to identify and capitalize on new sources of qualified leads.
Work alongside the marketing team to increase the number and quality of inbound leads.
Champion data integrity and accuracy using HubSpot to track activity and manage sales opportunities through the funnel.

What You’ll need

5+ years of experience as an Account Executive or in a similar sales role, selling technical or developer-focused products to technical audiences.
Familiarity with the machine learning, AI, or software development ecosystem, and an ability to grasp complex technical concepts.
Proven track record of meeting or exceeding revenue targets in a fast-paced startup environment.
Experience with outbound prospecting, qualifying leads, running demos, and closing deals is essential.
Ability to uncover customer pain points, articulate value propositions, and effectively address objections to drive solutions.
Strong interpersonal skills to work cross-functionally with leadership, product, engineering, and marketing teams.
Proficiency with HubSpot or a similar CRM to track activity, manage the sales pipeline, and ensure data integrity.
Solid understanding and application of a sales methodology (e.g., MEDDIC, Challenger, or Sandler) with the ability to tailor approaches to different customer needs and scenarios.

Compensation

This role offers $300K OTE, with a 50/50 base/variable split, in addition to meaningful equity.

Benefits and Perks

We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success. Benefits may vary by location, team, and role.

Benefits include:

Comprehensive medical, dental and vision coverage (U.S.); Private medical and dental insurance (U.K.)
Retirement and financial wellness support (U.S.); Pension contribution (U.K.)
Generous paid time off, plus holidays
Paid parental leave
Professional development support
Wellness and work-from-home stipends
Flexible work environment

At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.

Ready to apply?

Lightning AI

View all jobs →

Director of Engineering, Intelligent Messaging

Attentive · New York, NY

Apply now

Engineering New York, NY Posted May 7, 2026

Attentive® is the AI marketing platform for 1:1 personalization redefining the way brands and people connect. We’re the only marketing platform that combines powerful technology with human expertise to build authentic customer relationships. By unifying SMS, RCS, email, and push notifications, our AI-powered personalization engine delivers bespoke experiences that drive performance, revenue, and loyalty through real-time behavioral insights.

Recognized as the #1 provider in SMS Marketing by G2, Attentive partners with more than 8,000 customers across 70+ industries. Leading global brands like Crate and Barrel, Urban Outfitters, and Carter’s work with us to enable billions of interactions that power tens of billions in revenue for our customers.

With a distributed global workforce and employee hubs in New York City, San Francisco, London, and Sydney, Attentive’s team has been consistently recognized for its performance and culture. We’re proud to be included in Deloitte’s Fast 500 (four years running!), LinkedIn’s Top Startups, Forbes’ Cloud 100 (five years running!), Inc.’s Best Workplaces, and the Human Rights Campaign Foundation's Corporate Equality Index!

About the Role

We’re looking for a Director of Engineering to lead our Intelligent Messaging group—one of the most critical and high-impact areas at Attentive. This team powers the systems behind billions of personalized messages (SMS, email, push) sent every month, helping the world’s leading brands connect with consumers in smarter, more meaningful ways.

At the core of this is AI, machine learning, and real-time data. This allows us to drive personalization at massive scale - turning every message into an opportunity to engage, convert, and build long-term customer relationships.

In this role, you’ll lead multiple teams and play a key role in defining how AI shapes the future of messaging at Attentive. You’ll partner closely with Product and Engineering leadership to build and scale systems that are fast, reliable, and deeply intelligent. You’ll stay close to the work - guiding architecture, unblocking complex problems, and stepping in when it matters - while also building strong teams and developing great managers.

This is a role for someone who likes to operate deep in the systems, close to the people, and aligned with the business. You’ll own the technical direction of a high-scale, high-uptime platform and help us push what’s possible as we continue to grow.

This is a hybrid role based in NYC, with occasional travel to our SF office.

What You’ll Accomplish

You’ll own the delivery of cutting-edge, AI-powered consumer messaging experiences used by millions
You’ll manage and evolve a multi-team organization, build on our great culture, and set a high bar for engineering excellence
You'll oversee the technical strategy in multiple domains, supporting various layers of our messaging applications by using existing and emerging technology platforms
You’ll accelerate our engineering velocity using cutting-edge agentic and LLM tooling, while successfully managing safety and stability
You’lll collaborate with product, ML, design, and data science to shape the roadmap - not just execute on it
You’ll work directly with partner teams and stakeholders in the platform, go-to-market, and customer success organizations

Your Expertise

Above all else, you are technical and love to dive deep to understand architecture, code, and infrastructure. This is the most critical attribute for success at Attentive.
You have 10+ years of industry experience, including managing teams of 30+ engineers, and at least 2 years managing managers. From a technical perspective, you have 8+ years of experience in software engineering roles, ideally reaching staff level as an individual contributor.
You embrace agentic workflows, and understand the benefits, complexity and risks of the fast-moving AI ecosystem
You care about software quality and have a track record of building reliable, high-uptime systems, particularly in data-intensive environments
You’re comfortable operating in fast-moving, high growth environments, translating business needs into the right levels of implementation

What We Use

Our backend is Java / Kotlin / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Aurora, AirFlow, Postgres, and Redis, hosted via AWS
Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS, using tooling like Istio, Datadog, Terraform, CloudFlare, and Helm
Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
Our automation is driven by custom and open source machine learning models, industry-leading LLMs, lots of data and tech like Python, Metaflow, HuggingFace, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

The US base salary range for this full-time position is $250,000 - $350,000 annually + equity + benefits
Our salary ranges are determined by role, level and location

#LI-EF1

By applying for this position, your data will be processed as per Attentive's Privacy Policy.

Attentive Company Values

Default to Action - Move swiftly and with purpose

Be One Unstoppable Team - Rally as each other’s champions

Champion the Customer - Our success is defined by our customers' success

Act Like an Owner - Take responsibility for Attentive’s success

Learn more about AWAKE, Attentive’s collective of employee resource groups.

If you do not meet all the requirements listed here, we still encourage you to apply! No job description is perfect, and we may also have another opportunity that closely matches your skills and experience.

At Attentive, we know that our Company's strength lies in the diversity of our employees. Attentive is an Equal Opportunity Employer and we welcome applicants from all backgrounds. Our policy is to provide equal employment opportunities for all employees, applicants and covered individuals regardless of protected characteristics. We prioritize and maintain a fair, inclusive and equitable workplace free from discrimination, harassment, and retaliation. Attentive is also committed to providing reasonable accommodations for candidates with disabilities. If you need any assistance or reasonable accommodations, please let your recruiter know.

Ready to apply?

Apply to Attentive

Attentive

View all jobs →

Staff Machine Learning Engineer, ML Infrastructure

Unity Technologies · New York, NY, USA

Apply now

AI & Machine Learning USA-Mountain View Posted May 7, 2026

The opportunity
Unity Vector builds an offline ML platform that powers insight, experimentation, attribution, and AI-driven decision-making across the company.

Our systems operate at scale across batch and streaming data, supporting analytics, product intelligence, machine learning pipelines, and business operations. As data volume and complexity grow, our platform also supports large-scale model training, feature generation, and experimentation workflows that power production ML systems.

To support this growth, we need strong technical ownership to ensure our ML pipelines remain reliable, scalable, and architecturally sound.

We are seeking a staff ML engineer to design and evolve the large-scale offline platform. This role focuses on building reliable infrastructure for generating training datasets, orchestrating ML workflows, and enabling efficient, distributed model training at scale. You will work closely with ML engineers and platform teams to ensure our pipelines can efficiently handle growing data volumes and increasingly complex training workloads.

You will play a key role in shaping how model datasets are prepared as well as model training, validated, and delivered to distributed training systems, while ensuring the reliability, scalability, and performance of our offline ML platform.

What you'll be doing

Design and operate large-scale data pipelines that generate training datasets used for machine learning training and experimentation
Develop infrastructure that supports distributed training workflows using technologies such as Pytorch, Ray Data, and Ray Train, etc.
Integrate ML pipelines with workflow orchestration systems (e.g., Flyte, Airflow, or similar) to enable reliable multi-stage training workflows
Improve reproducibility and observability of ML pipelines through dataset validation, monitoring, and automated testing
Optimize performance and resource utilization across distributed compute systems used for data processing and model training
Partner closely with ML engineers to enable efficient large-scale experimentation and model iteration
Lead architectural improvements to ensure our offline ML pipelines remain scalable, reliable, and cost-efficient

What we're looking for

Strong experience building large-scale ML pipelines
Experience working with distributed computing frameworks such as Ray, Spark, Flink and familiarity in the Ray ecosystem (Ray Data, Ray Train) for distributed data processing and model training
Experience building infrastructure for training data generation, dataset preparation, or ML feature pipelines
Deep experience designing and operating production-grade data pipelines
Strong programming skills in Python and experience working with large-scale distributed workloads
Experience with modern data infrastructure (data lakes, warehouses, orchestration systems, streaming platforms)
Strong systems thinking, with the ability to reason about performance, scalability, reliability, and cost tradeoffs in distributed systems
Proven ability to lead technical direction and influence architectural decisions across teams without formal authority

Additional information

Relocation support is not available for this position

Benefits
At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.

Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.

While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program

Life at Unity
Unity [NYSE: U] is the world’s leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D — closing the gap between ideas and reality. For more information, please visit www.unity.com.

Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.

Your privacy is important to us. Please take a moment to review our Prospect Privacy Policy and Applicant Privacy Policy. Should you have any concerns about your privacy, please contact us at DPO@unity.com.

#SEN #LI-ED1

*Note: Certain locations require a good faith disclosure of the base salary range for the role. The actual salary for the successful candidate may differ based on location, experience, and other job-related factors.

Gross pay salary

$209,700—$283,800 USD

Ready to apply?

Apply to Unity Technologies

Unity Technologies

View all jobs →

Machine Learning Intern/Co-op (Fall 2026)

PathAI · Boston (Onsite), New York (Onsite) Preferred, or Remote

Apply now

Machine Learning PathAI Boston Posted May 7, 2026

Who We Are

PathAI's mission is to improve patient outcomes with AI-powered pathology. Our platform promises substantial improvements to the accuracy of diagnosis and the efficacy of treatment of diseases like cancer, leveraging modern approaches in machine learning and artificial intelligence. We have a track record of success in deploying AI algorithms for histopathology in translational research, pathology labs and clinical trials. Rigorous science and careful analysis is critical to the success of everything we do. Our team, composed of diverse employees with a wide range of backgrounds and experiences, is passionate about solving challenging problems and making a huge impact on patient outcomes.

Where You Fit

Our Intern/Co-op program is designed to give you a real-world view of what it's like to be a Machine Learning Engineer at PathAI. You will be embedded directly into our AI product and ML Core teams, working on active projects that have a direct impact on our technical roadmap and business goals.

You will collaborate with a cross-functional team of scientists, engineers, and product managers to translate clinical needs into scalable ML solutions. This is your chance to contribute to meaningful work that directly relates to patient outcomes.

Timeline: This opportunity is for Fall 2026. We are looking for interns/co-ops who can commit to 3-6 months at PathAI (4-6 months preferred).

Location: We have offices in Boston, MA and New York, NY and would prefer interns/co-ops who can work from one of those locations—however, we will also consider remote candidates (US based only).

What You’ll Do

Contribute to the design, development, and evaluation of machine learning models for our AI products, AI services and core ML models.
Work on subprojects derived from our ongoing ML product roadmap, focusing on areas like model improvements with novel techniques.
Partner with our MLOps and platform teams to help build and improve our ML pipelines.
Participate in experimental design, analysis, and team knowledge-sharing initiatives like design reviews, technical forums and journal clubs.

What You Bring

Currently pursuing a M.S., or Ph.D. in Computer Science, Electrical Engineering, Biomedical Engineering with a focus on Computer Vision and Machine Learning.
Strong programming skills in Python and hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow).
A solid grasp of the fundamentals of machine learning and/or computer vision.
Excellent communication skills and a desire to work in a highly collaborative, cross-functional environment.
A passion for our mission to improve patient outcomes.
[Nice-to-have] Any high impact contributions through any AI/ML publications, open-source projects and any AI based products.

We are looking for team players who are passionate about what they do and are willing to tackle any task to contribute to our goals. You could be exactly who we are looking for!

We Want To Hear From You

At PathAI, we are looking for individuals who are team players, are willing to do the work no matter how big or small it may be, and who are passionate about everything they do. If this sounds like you, even if you may not match the job description to a tee, we encourage you to apply. You could be exactly what we're looking for.
PathAI is an equal opportunity employer, dedicated to creating a workplace that is free of harassment and discrimination. We base our employment decisions on business needs, job requirements, and qualifications — that's all. We do not discriminate based on race, gender, religion, health, personal beliefs, age, family or parental status, or any other status. We don't tolerate any kind of discrimination or bias, and we are looking for teammates who feel the same way.

Ready to apply?

Apply to PathAI

PathAI

View all jobs →

Engineering Manager, Customer Growth

Attentive · New York, NY

Apply now

Engineering United States Posted May 7, 2026

Attentive® is the AI marketing platform for 1:1 personalization redefining the way brands and people connect. We’re the only marketing platform that combines powerful technology with human expertise to build authentic customer relationships. By unifying SMS, RCS, email, and push notifications, our AI-powered personalization engine delivers bespoke experiences that drive performance, revenue, and loyalty through real-time behavioral insights.

Recognized as the #1 provider in SMS Marketing by G2, Attentive partners with more than 8,000 customers across 70+ industries. Leading global brands like Crate and Barrel, Urban Outfitters, and Carter’s work with us to enable billions of interactions that power tens of billions in revenue for our customers.

With a distributed global workforce and employee hubs in New York City, San Francisco, London, and Sydney, Attentive’s team has been consistently recognized for its performance and culture. We’re proud to be included in Deloitte’s Fast 500 (four years running!), LinkedIn’s Top Startups, Forbes’ Cloud 100 (five years running!), Inc.’s Best Workplaces, and the Human Rights Campaign Foundation's Corporate Equality Index!

About the Role
The Onsite Customer Growth team builds the features that help Attentive’s customers grow directly on their websites. Our mission is to accelerate list growth and improve conversion by delivering creative, high performing onsite experiences powered by strong engineering and intelligent AI driven optimization.

We are looking for an experienced Engineering Manager who can lead a team of backend engineers in building scalable systems that support millions of daily interactions. In this role, you will guide the technical direction of the team, foster engineering excellence, and collaborate deeply with AI, data, product, and design partners to deliver impactful, high quality products.

This role blends technical leadership, people management, and hands on architectural oversight, making it ideal for a manager who enjoys developing engineers while driving execution and innovation.

What You’ll Accomplish

Lead, mentor, and grow a high performing engineering team responsible for building the backend systems powering onsite customer growth products
Set the technical vision and roadmap for backend services, APIs, and data driven systems that power personalized onsite experiences at scale
Partner closely with AI, data, and product teams to develop intelligent capabilities that improve performance and user experience
Ensure the reliability, scalability, and performance of the systems that support customer growth and real time user interactions
Drive best practices in design discussions, code reviews, architecture decision making, and operational excellence
Foster a learning oriented team culture that encourages collaboration, curiosity, ownership, and continuous improvement
Own delivery of key product initiatives, balancing long term platform investments with near term business objectives
Promote clean, maintainable, well tested code and high engineering standards across the team

Your Expertise

7+ years of professional backend software engineering experience, including at least two years managing or leading engineers
Strong proficiency in one or more modern programming languages such as Java, or Typescript
Experience designing and operating distributed systems, APIs, and microservice architectures at scale
Hands on familiarity with cloud platforms such as AWS and containerization technologies such as Docker or Kubernetes
Deep understanding of databases, messaging systems, or streaming technologies such as PostgreSQL, Redis, or Kafka
Track record of building reliable, scalable, high throughput systems that support customer facing products
Demonstrated ability to coach and develop engineers, drive team alignment, and create an inclusive, collaborative engineering environment
Strong communication and cross functional partnership skills, with the ability to work effectively with AI, data, product, and design teams
A mindset rooted in ownership, curiosity, and a passion for building meaningful systems that drive measurable customer impact

What We Use

Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS
Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

The US base salary range for this full-time position is $193,000 - $250,000 annually + equity + benefits
Our salary ranges are determined by role, level and location

#LI-MN1

By applying for this position, your data will be processed as per Attentive's Privacy Policy.

Attentive Company Values

Default to Action - Move swiftly and with purpose

Be One Unstoppable Team - Rally as each other’s champions

Champion the Customer - Our success is defined by our customers' success

Act Like an Owner - Take responsibility for Attentive’s success

Learn more about AWAKE, Attentive’s collective of employee resource groups.

If you do not meet all the requirements listed here, we still encourage you to apply! No job description is perfect, and we may also have another opportunity that closely matches your skills and experience.

At Attentive, we know that our Company's strength lies in the diversity of our employees. Attentive is an Equal Opportunity Employer and we welcome applicants from all backgrounds. Our policy is to provide equal employment opportunities for all employees, applicants and covered individuals regardless of protected characteristics. We prioritize and maintain a fair, inclusive and equitable workplace free from discrimination, harassment, and retaliation. Attentive is also committed to providing reasonable accommodations for candidates with disabilities. If you need any assistance or reasonable accommodations, please let your recruiter know.

Ready to apply?

Apply to Attentive

Attentive

View all jobs →

Machine Learning Scientist

The New York Times · New York, NY

Apply now

Data Science New York, NY Posted May 7, 2026

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for.

About the Role

The New York Times is a technology company committed to producing the world's most reliable and highest quality journalism. Our ability to do so relies on a talented team of expert technologists who help NYT learn from a tremendous abundance of data unique to this company.

The Algorithmic Recommendations and Audience Data Science team aims to help users discover content across the Times' website, apps and emails by applying algorithms that make use of information about our readers' behavior and our editorial judgment. We also build internal tools for the newsroom to better understand story performance and coverage trends. We are a group of machine learning scientists and data analysts that partner with teams across The New York Times. We are looking for a Machine Learning Scientist to join the team and apply machine learning methods to meet this challenge. You will report to a Lead Machine Learning Scientist, and collaborate with partners across the company.

Responsibilities:

You will reframe business and newsroom goals as machine learning tasks that deliver accurate predictions, relevant insights, and optimization
You will adapt or develop machine learning algorithms in cases when existing algorithms are insufficient, while implementing simple approaches when appropriate
You will implement and deploy machine learning research with robustness and reproducibility, with consideration of risks and trade-offs
You will turn models into data products, collaborate with engineering teams, and integrate into processes throughout The Times
You will communicate complex ideas in machine learning while collaborating with technical and non-technical colleagues in in engineering, analytics, product management, marketing, editorial, and executive leadership groups
Demonstrate support and understanding of our value of journalistic independence and a commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

PhD, MS + 2 years experience, or 3+ years work experience in machine learning, statistics, computational social science, applied mathematics, or another quantitative/computational discipline
2+ years experience with open source machine learning or statistical analysis tools
2+ years coding experience in Python
2+ years experience in SQL and manipulating large structured or unstructured datasets for analysis

Preferred Qualifications:

1+ year of experience with recommendation systems, using natural language processing and small and large language models.
1+ years of experience with deep learning architectures, fine-tuning, embeddings and Pytorch or Tensorflow
1+ years of experience translating ambiguous business questions into machine learning problems
1+ years of experience building data products, either internal or consumer-facing

REQ-020029

The annual base pay range for this role is between:

$121,000—$131,000 USD

For roles in the U.S., dependent on your role, you may be eligible for variable pay, such as an annual bonus and restricted stock. Benefits may include medical, dental and vision benefits, Flexible Spending Accounts (F.S.A.s), a company-matching 401(k) plan, paid vacation, paid sick days, paid parental leave, tuition reimbursement and professional development programs.

For roles outside of the U.S., information on benefits will be provided during the interview process.

The New York Times Company is committed to being the world’s best source of independent, reliable and quality journalism. To do so, we embrace a diverse workforce that has a broad range of backgrounds and experiences across our ranks, at all levels of the organization. We encourage people from all backgrounds to apply.

We are an Equal Opportunity Employer and do not discriminate on the basis of an individual's sex, age, race, color, creed, national origin, alienage, religion, marital status, pregnancy, sexual orientation or affectional preference, gender identity and expression, disability, genetic trait or predisposition, carrier status, citizenship, veteran or military status and other personal characteristics protected by law. All applications will receive consideration for employment without regard to legally protected characteristics. The U.S. Equal Employment Opportunity Commission (EEOC)’s Know Your Rights Poster is available here.

The New York Times Company will provide reasonable accommodations as required by applicable federal, state, and/or local laws. Individuals seeking an accommodation for the application or interview process should email reasonable.accommodations@nytimes.com. Emails sent for unrelated issues, such as following up on an application, will not receive a response.

The Company encourages those with criminal histories to apply, and will consider their applications in a manner consistent with applicable "Fair Chance" laws, including but not limited to the NYC Fair Chance Act, the Los Angeles Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.

For information about The New York Times' privacy practices for job applicants click here.

Please beware of fraudulent job postings. Scammers may post fraudulent job opportunities, and they may even make fraudulent employment offers. This is done by bad actors to collect personal information and money from victims. All legitimate job opportunities from The New York Times will be accessible through The New York Times careers site. The New York Times will not ask job applicants for financial information or for payment, and will not refer you to a third party to do so. You should never send money to anyone who suggests they can provide employment with The New York Times.

If you see a fake or fraudulent job posting, or if you suspect you have received a fraudulent offer, you can report it to The New York Times at NYTapplicants@nytimes.com. You can also file a report with the Federal Trade Commission or your state attorney general.

Ready to apply?

Apply to The New York Times

The New York Times

View all jobs →

Expression of Interest: Machine Learning Engineer

Moloco · Menlo Park, California, United States; New York, New York, United States; Seattle, Washington, United States

Apply now

Engineering Menlo Park - Office New York - Office Seattle - Office Posted May 6, 2026

About Moloco:

Moloco builds some of the most powerful AI advertising solutions in the world. Our name—short for "machine learning company"—reflects our core mission: democratizing access to the advanced AI that has historically been reserved for tech giants. Led by machine learning pioneers who built some of the most successful ad systems at Google, including YouTube's monetization engine and key search advertising technologies, we're transforming how businesses grow and compete in the digital economy.

Built with AI from day one, Moloco’s planet-scale machine learning platform powers a suite of solutions for advertising growth and monetization. Moloco Ads is an AI-powered platform that delivers real business outcomes for mobile app marketers through performance-based user acquisition. Moloco Commerce Media enables retailers and marketplaces to build revenue-generating ad businesses that balance user experience and advertiser performance.

Moloco is headquartered in Silicon Valley, with offices in Seattle, New York, San Francisco, Seoul, Beijing, Singapore, Gurgaon, Tokyo, Shanghai, London, Tel Aviv, and Berlin.

Moloco is a truly rewarding place to work and in an exciting period of growth, which you could be a part of. Join us today and apply now!

Expression of Interest

We know that for the most talented engineers, the right opportunity is about more than just a job title, it’s about the right challenge at the right time. Even if our current openings don't perfectly fit your timing and interests today, we still want to hear from you. We view this as a priority pathway to connect with curious, driven MLEs whose unique expertise can help us architect the next generation of planet-scale ML systems.

At Moloco, our mission is to empower the global digital economy by turning massive first-party data into measurable business outcomes. Whether it’s optimizing real-time bidding for Moloco Ads or building AI-native stacks for Streaming and Commerce, we’re looking for engineers to help us lead the shift toward a more performance-driven, AI-powered internet.

If you’re excited to scale and innovate in a fast-moving environment, share your profile and we will reach out the moment we see a potential match for your experiences and future goals.

About the Role

As a Machine Learning Engineer at Moloco, you will design, train, and deploy the large‑scale models that power our programmatic advertising and commerce media products. You will work at the heart of our real-time bidding and pricing systems, helping shape an end-to-end ML ecosystem that processes billions of daily events. Your work will directly improve marketplace performance for global advertisers and publishers by optimizing for relevance, ROI, and user experience at a scale few companies can match.

The Opportunity

Architect and iterate on high-performance models that improve ad relevance, click-through rates, and conversion performance.
Productionize and maintain scalable ML pipelines - from data ingestion to online inference - on top of planet-scale infrastructure.
Extract insights from massive datasets of user behavior and auction signals to define new features and refine modeling strategies.
Translate business goals (revenue, ROI, engagement) into concrete modeling challenges and success metrics in collaboration with Product and Data Science.
Validate innovation through rigorous experimentation, including A/B tests, offline evaluations, and counterfactual analyses.
Balance marketplace health by implementing models that harmonize advertiser value with a high-quality user experience.
Enhance system reliability by refining feature stores, monitoring data quality, and establishing robust debugging practices.
Drive platform evolution, contributing to ML tools and guidelines that increase experimentation velocity and deployment speed.
Optimize for performance, partnering with Infra teams to reduce latency and improve throughput for low-cost, high-scale decisioning.
Elevate technical excellence by sharing best practices in modeling and production ML with the broader engineering team.

Expertise We Value:

MLEs at Moloco are hands-on builders of some of the world’s highest-scale ML workloads. They bridge technical innovation with global revenue outcomes, owning the critical systems that define our next generation of machine learning and optimization platforms.

While every journey is unique, we find that the most successful MLEs at Moloco bring a deep technical foundation in the following areas:

Production ML at Scale: 5-12+ years of experience delivering ML solutions in high-stakes production environments (e.g., Ads, Recommenders, Search, or Marketplaces), with a track record of scaling models for massive throughput and low-latency requirements.
Algorithmic Mastery: A strong foundation in ML and statistics applied to real-world business challenges, with expertise in areas such as ranking, calibration, exploration-exploitation, causal inference, or multi‑objective optimization.
Full-Lifecycle Engineering: Deep understanding of the end-to-end ML lifecycle, including data pipelining, feature engineering, model architecture, inference optimization, and the deployment of models into online systems.
Technical Versatility: Proficiency across a modern ML toolkit (Python, SQL, and frameworks like TensorFlow or PyTorch) and experience leveraging data processing stacks like Spark, Beam, or Flink to deliver results at scale.
Operational Stewardship: Experience ensuring the long-term health of ML systems in live environments—monitoring performance, diagnosing drift, and iterating based on real-world feedback to maintain measurable impact.
Technical Mentorship: A passion for advancing the team’s collective bar by sharing best practices for large-scale ML systems and guiding the technical direction of complex machine learning initiatives.

Our Tech Stack:

Languages: Python, Go, C++
ML Frameworks: TensorFlow, PyTorch, JAX
Infrastructure: GCP, AWS, Kubernetes, Spark, BigQuery, BigTable

How You Work:

Your ethos is ownership

You thrive in ambiguity and enjoy partnering with others to shape vague requirements into clear roadmaps with pragmatic tradeoffs.
You take shared accountability for the end-to-end journey; communicating progress, surfacing risks early, and following through to ensure your work creates measurable value.

You demonstrate strong judgment under uncertainty.

You prioritize based on long-term impact, over short-term noise, making deliberate decisions when information is incomplete.
You explicitly weigh tradeoffs like speed vs. quality and remain agile enough to adjust your approach thoughtfully as new information/data emerges.

You lead through clarity and active listening.

You reduce ambiguity for the team by asking the right questions upfront, tailor your communication to your audience, document your decisions, and bring helpful structure to complex discussions.
You provide thoughtful, evidence-based feedback when needed and align behind decisions once they are made.

You collaborate early, instead of solving in isolation.

You build trust across the organization by listening first and navigate conflicting needs with empathy, creating buy-in around priorities and scope.
You navigate technical tensions productively, disagreeing thoughtfully while maintaining momentum and strengthening professional relationships.

You fall in love with the problem, not the solution

You build for the long run, looking beyond immediate tasks to understand root causes, second-order effects, and the long-term health of our ML ecosystem.
When something breaks, you don’t just patch it; you seek structural improvements that prevent recurrence and elevate the technical bar for the entire organization.

You prioritize customer impact and take action to make it real.

You prioritize effective solutions that drive business impact over technical elegance, spotting opportunities that others might overlook.
You have the initiative to turn ideas into outcomes and the agency to identify and fix gaps, even when they aren’t yet on the formal roadmap.

You can apply for this role through our Open Positions page (or through our Internal Job Board if you are a current employee). We will review submissions on an ongoing basis.

Our Compensation And Benefits (for United States Residents Only)

In accordance with various state laws, the range provided is a reasonable estimate of the base compensation for this role. The actual amount may be higher or lower based on non-discriminatory factors such as experience, knowledge, skills, and abilities. We also offer a competitive benefits package.

Base Pay Range:

$197,600—$420,000 USD

Moloco Thrive: Benefits and Well-Being:

We take care of you and create the conditions for you to do the best work of your career. Through a lens of inclusion, we offer innovative benefits that empower our employees to take care of themselves and their families so they can do the best work of their lives.

Moloco Values:

Lead with Humility: Everyone’s voice is respected, valued, and heard. With humility, we become more open and accessible to each other. We win, lose, and learn together. Accountability and feedback are essential to our success.
Uncapped Growth Mindset: We see all situations as opportunities to learn, grow, and improve as individuals and as an organization. We seek diverse perspectives, encourage curiosity, and promote experimentation to push the boundaries of what’s possible.
Create Real Value: We pursue the most impactful opportunities with rigor and integrity. We take intelligent risks and make disciplined trade-offs to maintain deep focus. We help our customers win by delivering durable value.
Go Further Together: We’re one team working towards one mission and vision. We collaborate proactively and inclusively, involving the right people at the right time and in the right way. We strive to create a more equitable workplace. We won’t let each other fail.

Additional Resources:

AI Use in Interviews

Our interview process is designed to get to know the real you. Unless a round specifically includes AI as part of what's being assessed, we ask that candidates engage without AI assistance. Please review our AI Use in Interviews Policy before your interview to understand what to expect. Failure to comply with this policy may impact your candidacy.

Equal Opportunity:

Creating a diverse workforce and a culture of inclusion and belonging is core to our existence. To reach our goals, diversity of talent and thought is a critical component of how we operate as an organization. Our workforce is our superpower, and we know that fostering a culture of inclusion, authenticity, and belonging gives us the greatest opportunity to achieve our vision to become the scaling engine for the Internet economy.

Moloco is an equal opportunity employer. We highly value diversity in our current and future employees and do not discriminate (including in our hiring and promotion practices) on the basis of race, color, creed, religion, national origin, age, sex and gender, gender expression and identity, sexual orientation, marital status, ancestry, physical or mental disability, military or veteran status, or any other characteristic protected by law.

Candidate Privacy Notice:

Your privacy matters to us. By applying, you acknowledge that you’ve reviewed our Candidate Privacy Notice.

Ready to apply?

Apply to Moloco

Moloco

View all jobs →

Research Engineer

Hudson River Trading · London, United Kingdom; New York, NY, United States

Apply now

Research & Development Platform London New York City Seattle Austin Boulder Chicago Posted May 6, 2026

Hudson River Trading (HRT) is a quantitative trading firm at the forefront of technological innovation. We build and deploy cutting-edge systems within one of the world’s most advanced computing environments to power our global trading operations. Our non-siloed, collaborative coding environment empowers talented engineers to make significant contributions and see their impact daily. At HRT, you'll be challenged to solve the most complex problems in trading alongside many of the brightest minds in the field.

We are seeking highly motivated and skilled Research Engineers who will work very closely with our Algo Developer (Quant Research) trading teams. These roles require exceptional programming fundamentals, a strong user focus, and the ability to thrive in a fast-paced environment with constantly evolving requirements. Multitasking and context switching are inherent aspects of this role, through which you will gain insight into the ideation and execution of some of the world's most sophisticated trading strategies.

Research Engineers at HRT work on a wide variety of projects. Examples include:

Designing highly customized quantitative systems that enable Algo Developers to easily express and backtest new predictive signals.
Building world-class research tooling to speed up Algo Developers’ research iteration.
Aiding the development and deployment of very large deep learning models for HRT’s live trading.
Improving HRT’s monetization systems which turn our predictions into profitable trades.
Evaluating sim vs. live differences to improve the fidelity of our simulations.
Building systems to monitor and manage live trading.
Specializing in specific time horizons, from high frequency trading to mid-to-low frequency hedge fund-style strategies.
Working across a very wide variety of asset classes (from equities to fixed income to options) and regions (from North America to Asia Pacific) – you’ll interact with markets across the world!

Responsibilities

Design, develop, and maintain robust, performant, and scalable software systems.
Optimize existing codebases for performance, reliability, and efficiency.
Debug complex issues across distributed systems in a time-sensitive environment.
Optimize both the mechanics and ergonomics of Algo Developer research workflows; this requires developing a deep intuition for research methodologies.
Balance the short term goals of individual trading teams with the longer term goals of HRT’s generalized trading platforms across trading teams. Because we don’t work in a pod environment, REs on different trading teams are expected to share technology and ideas.

Qualifications

Completed a Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. If you are currently pursuing your Bachelor's degree, please apply to our Campus/New Grad opportunities.
Previous experience at a top-tier finance or technology company with an excellent track record of rapid advancement and superlative reviews.
Experience with supporting internal users is preferred; bonus if you have real hands-on experience with quant research and/or ML/Deep Learning platforms.
Experience with python numerical, ML and data-oriented libraries is a big plus (e.g. pandas, scikit, pytorch, etc.)
Candidates should be prepared for technical interviews in either Python or C++. While there is no hard language requirement for RE roles, proficiency in one of these languages will be assessed during the interview process.
Kindness and empathy is a real requirement. No “smart jerks” at HRT.
Strong understanding of data structures, algorithms, and design principles.
Excellent communication skills, both written and verbal.
HRT ships every day. The ability to thoughtfully, methodically, and reliably deploy new software and features is a critical skill.
If you have management experience, that’s always a bonus – but even so, expect to code!

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

For more info about interviewing at HRT, see this blog!

Culture

Hudson River Trading (HRT) brings a scientific approach to trading financial products. We have built one of the world's most sophisticated computing environments for research and development. Our researchers are at the forefront of innovation in the world of algorithmic trading.

At HRT we welcome a variety of expertise: mathematics and computer science, physics and engineering, media and tech. We’re a community of self-starters who are motivated by the excitement of being at the cutting edge of automation in every part of our organization—from trading, to business operations, to recruiting and beyond. We value openness and transparency, and celebrate great ideas from HRT veterans and new hires alike. At HRT we’re friends and colleagues – whether we are sharing a meal, playing the latest board game, or writing elegant code. We embrace a culture of togetherness that extends far beyond the walls of our office.

Feel like you belong at HRT? Our goal is to find the best people and bring them together to do great work in a place where everyone is valued. HRT is proud of our diverse staff; we have offices all over the globe and benefit from our varied and unique perspectives. HRT is an equal opportunity employer; so whoever you are we’d love to get to know you.

Please be advised: Use of AI tools during interviews or assessments is strictly prohibited, unless otherwise instructed or agreed upon. We employ various methods to evaluate the authenticity of candidate responses. If we determine that AI assistance was used during any stage of the hiring process, we reserve the right to immediately disqualify your candidacy or rescind any job offers extended.

Ready to apply?

Apply to Hudson River Trading

Hudson River Trading

View all jobs →

Software Engineer - Treasury Infrastructure

Hudson River Trading · New York, NY, United States

Apply now

Research & Development Platform London New York City Seattle Austin Boulder Chicago Posted May 6, 2026

Hudson River Trading (HRT) is looking for a Senior Software Engineer to focus on our Treasury Infrastructure. Coders at HRT work on small, highly productive, and efficient teams that design, improve, and maintain the technology that powers worldwide trading — at HRT, the code you write is our business. You’ll have an opportunity to work closely with Treasury Quantitative Researchers and our Funding Team to design and develop HRT's Treasury Optimization and Research Platform.

We are looking for highly skilled programmers who love to code and solve complex problems, appreciate a culture of collaboration, and thrive in a performance-driven environment. You can always expect to be challenged by the ever-changing financial markets, and find yourself working on critical software in an extremely fast-paced, real-time environment.

Responsibilities

Contribute to the engineering design and development of HRT’s Treasury Optimization Platform.
Collaborate with Treasury Researchers on HRT’s Treasury Research Infrastructure.
Collaborate with Quantitative Developers as well as our Funding and Finance teams on managing cash and collateral requirements.

Qualifications

Completed a Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. If you are currently pursuing your Bachelor's degree, please apply to our Campus/New Grad opportunities.
Working experience in Python and good CS fundamentals.
Proficiency with numerical computing libraries (Numpy, PyTorch, TensorFlow) is a plus.
Knowledge of global portfolio financing and funding is a plus.
Strong problem-solving skills and ability to work in a fast-paced environment.
Excellent communication skills and ability to collaborate with engineers, researchers, and non-technical teams.

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

Culture

Hudson River Trading (HRT) brings a scientific approach to trading financial products. We have built one of the world's most sophisticated computing environments for research and development. Our researchers are at the forefront of innovation in the world of algorithmic trading.

At HRT we welcome a variety of expertise: mathematics and computer science, physics and engineering, media and tech. We’re a community of self-starters who are motivated by the excitement of being at the cutting edge of automation in every part of our organization—from trading, to business operations, to recruiting and beyond. We value openness and transparency, and celebrate great ideas from HRT veterans and new hires alike. At HRT we’re friends and colleagues – whether we are sharing a meal, playing the latest board game, or writing elegant code. We embrace a culture of togetherness that extends far beyond the walls of our office.

Feel like you belong at HRT? Our goal is to find the best people and bring them together to do great work in a place where everyone is valued. HRT is proud of our diverse staff; we have offices all over the globe and benefit from our varied and unique perspectives. HRT is an equal opportunity employer; so whoever you are we’d love to get to know you.

Please be advised: Use of AI tools during interviews or assessments is strictly prohibited, unless otherwise instructed or agreed upon. We employ various methods to evaluate the authenticity of candidate responses. If we determine that AI assistance was used during any stage of the hiring process, we reserve the right to immediately disqualify your candidacy or rescind any job offers extended.

Ready to apply?

Apply to Hudson River Trading

Hudson River Trading

View all jobs →

AI Researcher

Hudson River Trading · London, United Kingdom; New York, NY, United States; Seattle, Washington, United States

Apply now

Algo London New York City Seattle Posted May 6, 2026

Hudson River Trading (HRT) is hiring an AI Researcher to join the HAIL team. HAIL (HRT AI Labs) is the team at HRT responsible for developing and maintaining our most powerful models, which are used by our trading teams to drive a significant fraction of our trading. We are building and deploying "foundation models for markets", that ingest and train on vast amounts of market data, to make predictions about future market state. We are seeking experienced AI researchers to join our team to accelerate our efforts.

Researchers have great independence to pursue the research directions they think would be most impactful as part of a small focused team with minimal bureaucracy. They are enabled by state-of-the-art research clusters with very high GPU-to-researcher ratios, and supported by excellent engineering, hardware, and systems teams to realize their vision. Your work will be directly, clearly, highly impactful on the business, and it will be challenging: this is a field with no easy or obvious solutions. You'll be responsible for improving every part of our models: from featurization of data, to architecture design, to training dynamics, to how trading decisions are made.

Qualifications

Must have two or more years work experience in deep learning research, for any domain: robotics, biology, chemistry, physics, audio, video, etc.
Experience translating methods between areas of application is highly valued.
LLM experience is valuable, but not necessary.
Strong engineering skills valued, especially any of: GPU kernel development, lower-level Pytorch/JAX development, intermediate C++, FPGA/ASIC experience, HPC experience.

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience.

This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package which includes medical, dental, vision, basic life insurance, and enrollment in our company’s retirement savings plans. Employees will receive sick and parental leave, as well as other paid time off (including 20 vacation days and 10 paid holidays in the US). Please note that benefits and time off policies will vary across non-US locations.

Culture

Hudson River Trading (HRT) brings a scientific approach to trading financial products. We have built one of the world's most sophisticated computing environments for research and development. Our researchers are at the forefront of innovation in the world of algorithmic trading.

At HRT we welcome a variety of expertise: mathematics and computer science, physics and engineering, media and tech. We’re a community of self-starters who are motivated by the excitement of being at the cutting edge of automation in every part of our organization—from trading, to business operations, to recruiting and beyond. We value openness and transparency, and celebrate great ideas from HRT veterans and new hires alike. At HRT we’re friends and colleagues – whether we are sharing a meal, playing the latest board game, or writing elegant code. We embrace a culture of togetherness that extends far beyond the walls of our office.

Feel like you belong at HRT? Our goal is to find the best people and bring them together to do great work in a place where everyone is valued. HRT is proud of our diverse staff; we have offices all over the globe and benefit from our varied and unique perspectives. HRT is an equal opportunity employer; so whoever you are we’d love to get to know you.

Please be advised: Use of AI tools during interviews or assessments is strictly prohibited, unless otherwise instructed or agreed upon. We employ various methods to evaluate the authenticity of candidate responses. If we determine that AI assistance was used during any stage of the hiring process, we reserve the right to immediately disqualify your candidacy or rescind any job offers extended.

Ready to apply?

Apply to Hudson River Trading

Hudson River Trading

View all jobs →

Staff Software Engineer, Applied Training

CoreWeave · New York, NY / Sunnyvale, CA / Bellevue, WA

Apply now

Technology Sunnyvale, CA Bellevue, WA New York, NY Posted May 5, 2026

CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com.

What You’ll Do:

A lab signs with CoreWeave. They have thousands of GPUs waiting. Their first month? Spent on cluster setup instead of research. Building deployment scripts, fighting container images, wiring up job orchestration. They came to train models. Instead, they're doing operations.

This is the problem. We're building the Applied Training team to fix it.

You'll be an early member of a small team, responsible for our Kubernetes-native research cluster platform, or the sandbox client for agentic training and evaluation, or possibly a new project altogether. The goal is specific: Give every CoreWeave customer the research infrastructure that currently only exists inside frontier labs.

About the role:

Contribute to the roadmap for Applied Training. Figure out what actually unlocks new workloads and what's just nice to have. Work directly and closely with customers, and other teams inside of CoreWeave that are building cloud native primitives. Compute, storage, networking, etc.
For the research cluster platform: design and build a complete research cluster experience. CLI, job configuration schema, Kubernetes operators, daemons. Solve the problems researchers actually hit: code distribution, checkpoint-triggered evaluation, cross-cluster scheduling, programmatic job control. Replace the patchwork of scripts customers keep building on their own.
For sandbox infrastructure: own the Python SDK and work in a very tight loop with the backend team. When an RL training run needs to spawn thousands of isolated containers for agent rollouts, that's this system. When someone wants to run agent benchmarks at scale, that's this system. Make it work with our Kubernetes clusters, storage, and auth so researchers don't have to think about infrastructure.
Write the documentation for running popular OSS training frameworks on CoreWeave. The work that can unblock customers and help them succeed.
Work with infrastructure teams and customers directly. The customers are large AI labs running thousands of GPUs. Understand how they structure their internal supercomputing stacks. Bring that knowledge back to what we build.

Who You Are:

8-12+ years building distributed systems, ML infrastructure, or developer platforms.
Real Kubernetes experience: custom controllers, operators, scheduling, CRDs, workload orchestration at scale. Not just deploying things to Kubernetes or cluster administration.
Excited about rigorous engineering, but enabled by AI based workflows.
You understand what makes researchers productive. Code distribution matters. Fast iteration cycles matter. Workflows that don't require becoming infrastructure experts matter.
Familiarity with training: how distributed jobs get scheduled, how ranks initialize, what breaks at scale.
You've shipped infrastructure that other people rely on daily. Not prototypes. Production systems.
Good communicator. Can work with customers, translate researcher complaints into system designs.

Preferred:

Experience building internal ML platforms or research clusters at a company doing large-scale training.
Familiarity with agentic AI: RL training with rollouts, agent evaluation, sandbox isolation for running untrusted code.
Background with Slurm, Ray, or similar workload orchestration. Opinions on where they fall short.
Experience with container runtimes, isolation (gVisor, Kata), or serverless platforms.
OSS contributions to Kubernetes SIGs, Ray, PyTorch, or similar.

Wondering if you’re a good fit? We believe in investing in our people and value candidates who can bring their diverse experiences to our teams – even if you aren't a 100% skill or experience match.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

Be Curious at Your Core
Act Like an Owner
Empower Employees
Deliver Best-in-Class Client Experiences
Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for takeoff, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

The base salary range for this role is $165,000 to $242,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

What We Offer

The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location.

In addition to a competitive salary, we offer a variety of benefits to support your needs, including:

Medical, dental, and vision insurance - 100% paid for by CoreWeave
Company-paid Life Insurance
Voluntary supplemental life insurance
Short and long-term disability insurance
Flexible Spending Account
Health Savings Account
Tuition Reimbursement
Ability to Participate in Employee Stock Purchase Program (ESPP)
Mental Wellness Benefits through Spring Health
Family-Forming support provided by Carrot
Paid Parental Leave
Flexible, full-service childcare support with Kinside
401(k) with a generous employer match
Flexible PTO
Catered lunch each day in our office and data center locations
A casual work environment
A work culture focused on innovative disruption

Our Workplace

While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration.

California Consumer Privacy Act - California applicants only

CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.

As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com.

Export Control Compliance

This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.

Ready to apply?

CoreWeave

View all jobs →

Senior Software Engineer II, Applied Training

CoreWeave · New York, NY / Sunnyvale, CA / Bellevue, WA

Apply now

Technology Sunnyvale, CA Bellevue, WA New York, NY Posted May 5, 2026

CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com.

What You’ll Do:

A lab signs with CoreWeave. They have thousands of GPUs waiting. Their first month? Spent on cluster setup instead of research. Building deployment scripts, fighting container images, wiring up job orchestration. They came to train models. Instead, they're doing operations.

This is the problem. We're building the Applied Training team to fix it.

You'll be an early member of a small team, responsible for our Kubernetes-native research cluster platform, or the sandbox client for agentic training and evaluation, or possibly a new project altogether. The goal is specific: Give every CoreWeave customer the research infrastructure that currently only exists inside frontier labs.

About the role:

Contribute to the roadmap for Applied Training. Figure out what actually unlocks new workloads and what's just nice to have. Work directly and closely with customers, and other teams inside of CoreWeave that are building cloud native primitives. Compute, storage, networking, etc.
For the research cluster platform: design and build a complete research cluster experience. CLI, job configuration schema, Kubernetes operators, daemons. Solve the problems researchers actually hit: code distribution, checkpoint-triggered evaluation, cross-cluster scheduling, programmatic job control. Replace the patchwork of scripts customers keep building on their own.
For sandbox infrastructure: own the Python SDK and work in a very tight loop with the backend team. When an RL training run needs to spawn thousands of isolated containers for agent rollouts, that's this system. When someone wants to run agent benchmarks at scale, that's this system. Make it work with our Kubernetes clusters, storage, and auth so researchers don't have to think about infrastructure.
Write the documentation for running popular OSS training frameworks on CoreWeave. The work that can unblock customers and help them succeed.
Work with infrastructure teams and customers directly. The customers are large AI labs running thousands of GPUs. Understand how they structure their internal supercomputing stacks. Bring that knowledge back to what we build.

Who You Are:

5-8+ years building distributed systems, ML infrastructure, or developer platforms.
Real Kubernetes experience: custom controllers, operators, scheduling, CRDs, workload orchestration at scale. Not just deploying things to Kubernetes or cluster administration.
Excited about rigorous engineering, but enabled by AI based workflows.
You understand what makes researchers productive. Code distribution matters. Fast iteration cycles matter. Workflows that don't require becoming infrastructure experts matter.
Familiarity with training: how distributed jobs get scheduled, how ranks initialize, what breaks at scale.
You've shipped infrastructure that other people rely on daily. Not prototypes. Production systems.
Good communicator. Can work with customers, translate researcher complaints into system designs.

Preferred:

Experience building internal ML platforms or research clusters at a company doing large-scale training.
Familiarity with agentic AI: RL training with rollouts, agent evaluation, sandbox isolation for running untrusted code.
Background with Slurm, Ray, or similar workload orchestration. Opinions on where they fall short.
Experience with container runtimes, isolation (gVisor, Kata), or serverless platforms.
OSS contributions to Kubernetes SIGs, Ray, PyTorch, or similar.

Wondering if you’re a good fit? We believe in investing in our people and value candidates who can bring their diverse experiences to our teams – even if you aren't a 100% skill or experience match.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

Be Curious at Your Core
Act Like an Owner
Empower Employees
Deliver Best-in-Class Client Experiences
Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for takeoff, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

The base salary range for this role is $139,000 to $204,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

What We Offer

The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location.

In addition to a competitive salary, we offer a variety of benefits to support your needs, including:

Medical, dental, and vision insurance - 100% paid for by CoreWeave
Company-paid Life Insurance
Voluntary supplemental life insurance
Short and long-term disability insurance
Flexible Spending Account
Health Savings Account
Tuition Reimbursement
Ability to Participate in Employee Stock Purchase Program (ESPP)
Mental Wellness Benefits through Spring Health
Family-Forming support provided by Carrot
Paid Parental Leave
Flexible, full-service childcare support with Kinside
401(k) with a generous employer match
Flexible PTO
Catered lunch each day in our office and data center locations
A casual work environment
A work culture focused on innovative disruption

Our Workplace

While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration.

California Consumer Privacy Act - California applicants only

CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.

As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com.

Export Control Compliance

This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.

Ready to apply?

CoreWeave

View all jobs →

AI Solutions Engineer, Post Sales Scale - W&B

CoreWeave · Livingston, NJ / New York, NY / Sunnyvale, CA / Bellevue, WA / Philadelphia, PA

Apply now

Global Field Organization San Francisco, CA Sunnyvale, CA Bellevue, WA Livingston, NJ New York, NY Philadelphia, PA Posted May 5, 2026

CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com.

What You’ll Do
The Field Engineering team at Weights & Biases plays a vital role in ensuring customer success and adoption of our platform. As part of this team, we partner with Sales, Support, Product, and Engineering to lead technical success after the sales process. We work closely with some of the most advanced AI teams in the world, helping them build, optimize, and scale their ML and GenAI workflows across industries such as computer vision, robotics, natural language processing, and large language models (LLMs).

About the Role

We’re hiring a Post-Sales AI Solutions Engineer (AISE), Scale Customer Success to help customers successfully implement and scale AI/ML workflows and GenAI/agentic applications on Weights & Biases. You will design and deliver technical enablement and adoption programs that reach many customers at once, create reusable assets that improve self-serve success, and use product signals and feedback loops to continuously improve outcomes.

Key Responsibilities

Run 1-to-many onboarding and enablement programs
Own and deliver scalable onboarding and adoption motions (webinars, cohort sessions, group training, and office hours) that help customers get to value quickly and consistently.
Build reusable technical assets that drive self-serve success
Create and maintain playbooks, reference architectures, templates, sample code/notebooks, and troubleshooting guides that standardize best practices and reduce repeated 1:1 work.
Operate the scaled motion using signals and feedback loops
Use product usage signals and customer patterns to segment and trigger the right interventions, track program impact (activation, time-to-first-value, feature adoption), and feed recurring insights back to Support, Product, and Field Engineering to continuously improve the scaled journey.

Who You Are

3–5 years of relevant experience in a similar role
Strong programming proficiency in Python
Experience with deep learning frameworks (TensorFlow/Keras, PyTorch Lightning) and tools (e.g., Streamlit, LangChain)
Familiarity with cloud platforms (AWS, GCP, Azure)
Excellent communication and presentation skills, both written and verbal
Organized and outcomes-driven: you can run programs, measure impact, and iterate.

Preferred

Experience with GenAI and LLMs
Proficiency with HuggingFace, Fastai, scikit-learn, XGBoost, LightGBM, or Ray
Experience with hyperparameter optimization solutions
Background in data engineering, MLOps, or LLMOps, with tools such as Docker and Kubernetes
Familiarity with data pipeline tools

Wondering if you’re a good fit?
We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.

You love collaborating with top AI teams to solve real-world ML and GenAI challenges
You’re curious about how to optimize AI workflows at scale
You’re an expert in Python and ML tooling, with a passion for enabling customer success

Why Us?
We work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

Be Curious at Your Core
Act Like an Owner
Empower Employees
Deliver Best-in-Class Client Experiences
Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for takeoff, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

The base salary range for this role is $139,000 to $204,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

What We Offer

The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location.

In addition to a competitive salary, we offer a variety of benefits to support your needs, including:

Medical, dental, and vision insurance - 100% paid for by CoreWeave
Company-paid Life Insurance
Voluntary supplemental life insurance
Short and long-term disability insurance
Flexible Spending Account
Health Savings Account
Tuition Reimbursement
Ability to Participate in Employee Stock Purchase Program (ESPP)
Mental Wellness Benefits through Spring Health
Family-Forming support provided by Carrot
Paid Parental Leave
Flexible, full-service childcare support with Kinside
401(k) with a generous employer match
Flexible PTO
Catered lunch each day in our office and data center locations
A casual work environment
A work culture focused on innovative disruption

Our Workplace

While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration.

California Consumer Privacy Act - California applicants only

CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.

As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com.

Export Control Compliance

This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.

Ready to apply?

CoreWeave

View all jobs →

Account Manager (W&B)

CoreWeave · San Francisco, CA / Sunnyvale, CA / New York, NY / Livingston, NJ

Apply now

Global Field Organization San Francisco, CA Sunnyvale, CA Posted May 5, 2026

CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com.

What You’ll Do:

The Account Manager owns the commercial and relationship aspects of the post-sales journey across a portfolio of Digital Native and select Enterprise customers. You will drive renewals, identify and close upsell and cross-sell opportunities, and ensure customers achieve measurable adoption outcomes with Weights & Biases (W&B). You’ll partner closely with Field Engineering (FE)—who leads technical success—while you lead the commercial motions including renewal execution, usage-to-value alignment, growth pipeline creation, and multi-threaded stakeholder engagement.

About the role:

You will own renewals and lead commercial execution across your assigned accounts, including identifying and closing upsell and cross-sell opportunities. You will partner closely with Field Engineering (FE) while running the commercial motions: renewal execution, usage-to-value alignment, growth pipeline creation, and multi-threaded stakeholder engagement. You will maintain detailed account plans (account maps, whitespace, usage trends, risks, and growth opportunities) and maintain weekly forecasting accuracy and CRM hygiene across renewals and growth motions. This role requires comfort engaging highly technical personas (ML engineers, researchers, PhDs) and operating with autonomy in a rapidly evolving AI ecosystem; it is not a playbook-driven role.

Own renewals, upsells, and cross-sells across your assigned accounts.
Build and maintain detailed account plans including account maps, whitespace, usage trends, risks, and growth opportunities.
Generate growth pipeline by identifying new use cases, teams, and product opportunities within existing accounts.

Who You Are:

Based in the Bay Area (San Francisco, Peninsula, South Bay) strongly preferred; secondary options: New York City or Northern NJ.
6+ years in B2B/SaaS customer-facing roles commercializing technical products.
3+ years in a quota-carrying Account Management, Sales, or Renewals role owning post-sales outcomes.
Strong, genuine interest in AI/ML and the evolving machine learning ecosystem.
High technical and product curiosity; comfortable speaking with developers, ML engineers, and researchers.
Proven ability to drive growth motions (upsells, cross-sells) and manage retention in technical accounts.
Strong operational discipline: forecasting accuracy, CRM hygiene, renewal cadence management.
Thrives in ambiguity; able to self-direct and operate independently without detailed playbooks.

Preferred:

Experience working with ML, MLOps, DevOps, or data infrastructure teams.
Familiarity with Git, Jupyter, Python, PyTorch, or cloud platforms (AWS, GCP, Azure).
Experience designing or executing account activation or expansion strategies.
Exposure to AI-native companies, model builders, or generative AI workflows.

Wondering if you’re a good fit?

We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren’t a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.

You love owning renewals and growth motions while building multi-threaded stakeholder relationships.
You’re curious about AI/ML and enjoy learning quickly in a rapidly evolving ecosystem.
You’re an expert in operating with strong discipline across account plans, forecasting, and CRM hygiene to drive commercial outcomes.

The base salary range for this role is $95,000 to $130,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

What We Offer

The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location.

In addition to a competitive salary, we offer a variety of benefits to support your needs, including:

Medical, dental, and vision insurance - 100% paid for by CoreWeave
Company-paid Life Insurance
Voluntary supplemental life insurance
Short and long-term disability insurance
Flexible Spending Account
Health Savings Account
Tuition Reimbursement
Ability to Participate in Employee Stock Purchase Program (ESPP)
Mental Wellness Benefits through Spring Health
Family-Forming support provided by Carrot
Paid Parental Leave
Flexible, full-service childcare support with Kinside
401(k) with a generous employer match
Flexible PTO
Catered lunch each day in our office and data center locations
A casual work environment
A work culture focused on innovative disruption

Our Workplace

While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration.

California Consumer Privacy Act - California applicants only

CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.

As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com.

Export Control Compliance

This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.

Ready to apply?

CoreWeave

View all jobs →

Data Science Manager, Machine Learning - Lyft Ads

Lyft · New York, NY

Apply now

Lyft Ads San Francisco Office New York Office Posted May 5, 2026

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

ML & Data Science is at the heart of Lyft's products and decision-making. ML and Data Science professionals at Lyft operate in dynamic environments, moving quickly to build the world's best transportation solutions. We tackle a wide range of challenges—from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products.

Lyft Ads is Lyft's advertising platform, connecting brands with high-intent audiences across the rideshare journey. Our offerings span in-app ad formats, in-car tablet experiences, bikeshare and station sponsorships, and programmatic integrations—enabling advertisers to reach riders at key moments of engagement. These products power high-impact use cases across brand awareness, performance marketing, audience targeting, and measurement for enterprise advertisers.

We are seeking an Algorithms Science Manager to lead a team of Data Scientists, Applied Scientists, and Machine Learning Engineers building the algorithmic backbone of Lyft Media. In this role, you will shape the vision, define the roadmap, and drive execution for projects that improve ad relevance, optimize yield, enhance targeting and measurement, and deliver measurable value to our advertising partners. You'll collaborate closely with Product, Engineering, Design, and Sales teams to build models, experimentation frameworks, and production ML systems that inform strategy and power product innovation.

This is a high-visibility, high-impact role with direct influence on Lyft's advertising platform and revenue growth. The ideal candidate will bring deep expertise in algorithm development, machine learning, causal inference, and experimentation; strong business acumen in ads or marketplace contexts; and a proven track record of leading multi-disciplinary technical teams in fast-paced, cross-functional environments.

Responsibilities:

Lead, mentor, and grow a high-performing, multi-disciplinary team spanning Applied Science. Data Science, and Machine Learning Engineering for Lyft Media.
Define and execute the technical vision and roadmap for the team, ensuring alignment with overall business strategy and revenue goals across research, modeling, and production ML.
Design, develop, and deploy algorithms and ML systems that power core advertising capabilities—including ad targeting, audience segmentation, bid optimization, attribution, and yield management.
Partner with Product, Engineering, and Design to integrate solutions into scalable, production-grade ad serving and measurement systems.
Establish robust experimentation and causal inference frameworks to measure the impact of algorithmic changes on advertiser outcomes, rider experience, and platform revenue.
Bridge the gap between research and production—ensuring that applied science innovations translate into reliable, maintainable ML systems at scale.
Conduct deep analyses of complex, large-scale datasets to uncover opportunities for revenue growth, advertiser performance improvement, and enhanced user experience.
Champion data-driven decision-making, ensuring that product and go-to-market decisions are informed by rigorous quantitative analysis.
Drive innovation by staying current with emerging research, technologies, and industry best practices in computational advertising, optimization, and applied machine learning.

Experience:

PhD (preferred) or Master's degree in a quantitative field such as Machine Learning, Computer Science, Statistics, Engineering, or a related discipline; or equivalent practical experience.
8+ years of progressive experience in machine learning, optimization, or causal inference, including building and deploying algorithms in production systems.
3+ years of people management experience leading multi-disciplinary technical teams (data science, applied science, and/or ML engineering), with a proven ability to mentor, develop, and retain top talent.
Demonstrated ability to set a strategic vision for a technical team and translate it into impactful, scalable solutions that drive measurable business outcomes.
Deep expertise in machine learning, experimental design, causal inference, and statistical methodologies, with a track record of applying them to high-stakes product or marketplace decisions.
Strong understanding of ML engineering best practices—model training infrastructure, feature pipelines, model serving, and monitoring in production environments.
Experience in advertising technology, media measurement, or marketplace optimization is strongly preferred.
Experience navigating complex, ambiguous problem spaces and guiding teams through prioritization, tradeoffs, and execution.
Strong communication and influence skills, with the ability to engage both technical and executive stakeholders, align priorities, and build consensus.
Hands-on proficiency with large-scale data processing tools and machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn).

Benefits:

Great medical, dental, and vision insurance options with additional programs available when enrolled
Mental health benefits
Family building benefits
Child care and pet benefits
401(k) plan with company match to help save for your future
In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
Subsidized commuter benefits
Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the New York City area is $148,000 - $185,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Ready to apply?

Lyft

View all jobs →

Data Science Manager, Machine Learning - Lyft Ads

Lyft · San Francisco, CA

Apply now

Lyft Ads San Francisco Office New York Office Posted May 5, 2026

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

ML & Data Science is at the heart of Lyft's products and decision-making. ML and Data Science professionals at Lyft operate in dynamic environments, moving quickly to build the world's best transportation solutions. We tackle a wide range of challenges—from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products.

Lyft Ads is Lyft's advertising platform, connecting brands with high-intent audiences across the rideshare journey. Our offerings span in-app ad formats, in-car tablet experiences, bikeshare and station sponsorships, and programmatic integrations—enabling advertisers to reach riders at key moments of engagement. These products power high-impact use cases across brand awareness, performance marketing, audience targeting, and measurement for enterprise advertisers.

We are seeking an Algorithms Science Manager to lead a team of Data Scientists, Applied Scientists, and Machine Learning Engineers building the algorithmic backbone of Lyft Media. In this role, you will shape the vision, define the roadmap, and drive execution for projects that improve ad relevance, optimize yield, enhance targeting and measurement, and deliver measurable value to our advertising partners. You'll collaborate closely with Product, Engineering, Design, and Sales teams to build models, experimentation frameworks, and production ML systems that inform strategy and power product innovation.

This is a high-visibility, high-impact role with direct influence on Lyft's advertising platform and revenue growth. The ideal candidate will bring deep expertise in algorithm development, machine learning, causal inference, and experimentation; strong business acumen in ads or marketplace contexts; and a proven track record of leading multi-disciplinary technical teams in fast-paced, cross-functional environments.

Responsibilities:

Lead, mentor, and grow a high-performing, multi-disciplinary team spanning Applied Science. Data Science, and Machine Learning Engineering for Lyft Media.
Define and execute the technical vision and roadmap for the team, ensuring alignment with overall business strategy and revenue goals across research, modeling, and production ML.
Design, develop, and deploy algorithms and ML systems that power core advertising capabilities—including ad targeting, audience segmentation, bid optimization, attribution, and yield management.
Partner with Product, Engineering, and Design to integrate solutions into scalable, production-grade ad serving and measurement systems.
Establish robust experimentation and causal inference frameworks to measure the impact of algorithmic changes on advertiser outcomes, rider experience, and platform revenue.
Bridge the gap between research and production—ensuring that applied science innovations translate into reliable, maintainable ML systems at scale.
Conduct deep analyses of complex, large-scale datasets to uncover opportunities for revenue growth, advertiser performance improvement, and enhanced user experience.
Champion data-driven decision-making, ensuring that product and go-to-market decisions are informed by rigorous quantitative analysis.
Drive innovation by staying current with emerging research, technologies, and industry best practices in computational advertising, optimization, and applied machine learning.

Experience:

PhD (preferred) or Master's degree in a quantitative field such as Machine Learning, Computer Science, Statistics, Engineering, or a related discipline; or equivalent practical experience.
8+ years of progressive experience in machine learning, optimization, or causal inference, including building and deploying algorithms in production systems.
3+ years of people management experience leading multi-disciplinary technical teams (data science, applied science, and/or ML engineering), with a proven ability to mentor, develop, and retain top talent.
Demonstrated ability to set a strategic vision for a technical team and translate it into impactful, scalable solutions that drive measurable business outcomes.
Deep expertise in machine learning, experimental design, causal inference, and statistical methodologies, with a track record of applying them to high-stakes product or marketplace decisions.
Strong understanding of ML engineering best practices—model training infrastructure, feature pipelines, model serving, and monitoring in production environments.
Experience in advertising technology, media measurement, or marketplace optimization is strongly preferred.
Experience navigating complex, ambiguous problem spaces and guiding teams through prioritization, tradeoffs, and execution.
Strong communication and influence skills, with the ability to engage both technical and executive stakeholders, align priorities, and build consensus.
Hands-on proficiency with large-scale data processing tools and machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn).

Benefits:

Great medical, dental, and vision insurance options with additional programs available when enrolled
Mental health benefits
Family building benefits
Child care and pet benefits
401(k) plan with company match to help save for your future
In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
Subsidized commuter benefits
Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $148,000 - $185,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Ready to apply?

Lyft

View all jobs →

Data Scientist, Algorithms - Lyft Ads

Lyft · New York, NY

Apply now

Lyft Ads New York Office Posted May 5, 2026

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

Lyft Ads is one of Lyft’s newest and fastest-growing businesses, focused on building the world’s largest transportation media network. Our mission is to help brands reach riders during key moments of their journey—before, during, and after a ride—by delivering meaningful, contextually relevant ad experiences. We operate at the intersection of mobility data, real-time decision systems, and AI-powered personalization, enabling advertisers to run high-impact campaigns with measurable outcomes.

We are seeking an Algorithms Scientist to help build the next generation of ads relevance, targeting, optimization, and measurement algorithms that power the Lyft Ads platform. In this role, you will work across large-scale datasets and complex real-time systems to design, prototype, and deploy production-grade machine learning models. You’ll collaborate closely with Engineering, Product, Data Science, and Sales to translate ambiguous business and advertiser needs into rigorous algorithmic solutions that improve ad performance, enhance marketplace efficiency, and drive meaningful revenue growth.

This is a high-impact, highly technical role within a rapidly scaling business line. The ideal candidate brings strong applied machine learning intuition, hands-on modeling experience, and the ability to write clean, efficient production code. You will play a critical role in shaping how advertisers connect with Lyft riders—pushing the boundaries of personalization, measurement, and real-time optimization in a dynamic marketplace.

Responsibilities:

Design, develop, and deploy production-grade machine learning models and algorithms that power core Lyft Ads capabilities, such as ad relevance, targeting, ranking, bid optimization, pacing, campaign delivery, and measurement.
Own the end-to-end lifecycle of modeling projects — including problem definition, data exploration, feature engineering, model development, offline evaluation, deployment, and monitoring.
Collaborate closely with Ads Engineering to integrate models into real-time ad-serving and batch decision systems, ensuring performance across latency, scalability, and reliability constraints.
Analyze large-scale mobility, behavioral, and ads performance datasets to identify patterns, surface opportunities, and guide ML and AI driven product improvements.
Implement rigorous model evaluation frameworks, including offline metrics, statistical tests, calibration, sensitivity analysis, and A/B experimentation to validate both model impact and system-level outcomes.
Build robust training pipelines, feature transformations, and scoring infrastructure, ensuring reproducibility, observability, and long-term maintainability.
Partner with Product, Engineering, and Sales to translate ambiguous advertiser goals (e.g., increased conversions, reach efficiency, brand lift) into measurable requirements and success metrics.
Investigate and resolve model behavior issues, production regressions, calibration drift, and performance anomalies in close partnership with Ads Infra teams.
Drive innovation by staying current with advances in ML for ranking, recommendation, causal inference, optimization, and ads measurement — and proactively identifying opportunities to apply them.
Contribute to Lyft Ads’ modeling and experimentation infrastructure, through model cards, documentation, reproducibility standards, and code quality improvements.

Experience:

Master’s, or PhD in Machine Learning, Computer Science, Statistics, Applied Mathematics, Engineering, or related quantitative fields; or equivalent applied industry experience.
3–5 years of hands-on ML/applied science experience, ideally involving production models, large-scale systems, or ads/recommendation/relevance domains.
Strong proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, JAX, or scikit-learn; ability to write clean, efficient, production-adjacent code.
Experience working with large-scale datasets and distributed data tools (Spark, Snowflake, Presto, Databricks).
Practical experience building and evaluating:

Ranking and relevance models
Optimization or pacing algorithms
Predictive models for CTR, CVR, or user response
Causal or experimentation-based measurement methods

Understanding of online/offline evaluation techniques, including:

Offline metrics (AUC, NDCG, MRR, calibration)
A/B testing methodologies
Bias correction and counterfactual estimation

Ability to solve ambiguous problems by structuring analyses, evaluating trade-offs, and proposing algorithmic solutions grounded in scientific rigor.
Strong communication skills, with an ability to clearly explain model behavior, constraints, trade-offs, and recommendations to engineering, product, and sales partners.
Demonstrated ownership of modeling work, including debugging, monitoring, documentation, and iteration after deployment.
Curiosity, initiative, and a track record of delivering measurable improvements through high-quality modeling.

Benefits:

Great medical, dental, and vision insurance options with additional programs available when enrolled
Mental health benefits
Family building benefits
Child care and pet benefits
401(k) plan to help save for your future
In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
Subsidized commuter benefits
Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the New York City area is $128,000 - $160,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Total compensation is dependent on a variety of factors, including qualifications, experience, and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Ready to apply?

Lyft

View all jobs →

Data Scientist, Algorithms - Lyft Ads

Lyft · San Francisco, CA

Apply now

Lyft Ads New York Office Posted May 5, 2026

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

Lyft Ads is one of Lyft’s newest and fastest-growing businesses, focused on building the world’s largest transportation media network. Our mission is to help brands reach riders during key moments of their journey—before, during, and after a ride—by delivering meaningful, contextually relevant ad experiences. We operate at the intersection of mobility data, real-time decision systems, and AI-powered personalization, enabling advertisers to run high-impact campaigns with measurable outcomes.

We are seeking an Algorithms Scientist to help build the next generation of ads relevance, targeting, optimization, and measurement algorithms that power the Lyft Ads platform. In this role, you will work across large-scale datasets and complex real-time systems to design, prototype, and deploy production-grade machine learning models. You’ll collaborate closely with Engineering, Product, Data Science, and Sales to translate ambiguous business and advertiser needs into rigorous algorithmic solutions that improve ad performance, enhance marketplace efficiency, and drive meaningful revenue growth.

This is a high-impact, highly technical role within a rapidly scaling business line. The ideal candidate brings strong applied machine learning intuition, hands-on modeling experience, and the ability to write clean, efficient production code. You will play a critical role in shaping how advertisers connect with Lyft riders—pushing the boundaries of personalization, measurement, and real-time optimization in a dynamic marketplace.

Responsibilities:

Design, develop, and deploy production-grade machine learning models and algorithms that power core Lyft Ads capabilities, such as ad relevance, targeting, ranking, bid optimization, pacing, campaign delivery, and measurement.
Own the end-to-end lifecycle of modeling projects — including problem definition, data exploration, feature engineering, model development, offline evaluation, deployment, and monitoring.
Collaborate closely with Ads Engineering to integrate models into real-time ad-serving and batch decision systems, ensuring performance across latency, scalability, and reliability constraints.
Analyze large-scale mobility, behavioral, and ads performance datasets to identify patterns, surface opportunities, and guide ML and AI driven product improvements.
Implement rigorous model evaluation frameworks, including offline metrics, statistical tests, calibration, sensitivity analysis, and A/B experimentation to validate both model impact and system-level outcomes.
Build robust training pipelines, feature transformations, and scoring infrastructure, ensuring reproducibility, observability, and long-term maintainability.
Partner with Product, Engineering, and Sales to translate ambiguous advertiser goals (e.g., increased conversions, reach efficiency, brand lift) into measurable requirements and success metrics.
Investigate and resolve model behavior issues, production regressions, calibration drift, and performance anomalies in close partnership with Ads Infra teams.
Drive innovation by staying current with advances in ML for ranking, recommendation, causal inference, optimization, and ads measurement — and proactively identifying opportunities to apply them.
Contribute to Lyft Ads’ modeling and experimentation infrastructure, through model cards, documentation, reproducibility standards, and code quality improvements.

Experience:

Master’s, or PhD in Machine Learning, Computer Science, Statistics, Applied Mathematics, Engineering, or related quantitative fields; or equivalent applied industry experience.
3–5 years of hands-on ML/applied science experience, ideally involving production models, large-scale systems, or ads/recommendation/relevance domains.
Strong proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, JAX, or scikit-learn; ability to write clean, efficient, production-adjacent code.
Experience working with large-scale datasets and distributed data tools (Spark, Snowflake, Presto, Databricks).
Practical experience building and evaluating:

Ranking and relevance models
Optimization or pacing algorithms
Predictive models for CTR, CVR, or user response
Causal or experimentation-based measurement methods

Understanding of online/offline evaluation techniques, including:

Offline metrics (AUC, NDCG, MRR, calibration)
A/B testing methodologies
Bias correction and counterfactual estimation

Ability to solve ambiguous problems by structuring analyses, evaluating trade-offs, and proposing algorithmic solutions grounded in scientific rigor.
Strong communication skills, with an ability to clearly explain model behavior, constraints, trade-offs, and recommendations to engineering, product, and sales partners.
Demonstrated ownership of modeling work, including debugging, monitoring, documentation, and iteration after deployment.
Curiosity, initiative, and a track record of delivering measurable improvements through high-quality modeling.

Benefits:

Great medical, dental, and vision insurance options with additional programs available when enrolled
Mental health benefits
Family building benefits
Child care and pet benefits
401(k) plan to help save for your future
In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
Subsidized commuter benefits
Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $128,000 - $160,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Total compensation is dependent on a variety of factors, including qualifications, experience, and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Ready to apply?