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.

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

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.

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.

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.

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

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

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

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

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

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

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.

The Impact You’ll Be Contributing to Moloco:

As a Senior Machine Learning Engineer on Moloco’s Ads Quality team, you’ll design and scale machine learning systems that directly improve ad relevance, ranking, and optimization. Your work will have a measurable impact on advertiser performance, revenue efficiency, and the overall user experience across Moloco’s ad platform.

The Opportunity:

• Design, build, and deploy large-scale ML systems for ad ranking, click-through prediction, and conversion optimization
• Develop and operate production pipelines that process hundreds of millions of ad requests per day with low-latency requirements
• Collaborate directly with customers and partners in Mandarin to understand business goals and deliver data-driven ML solutions
• Apply systematic, reproducible approaches to model training, evaluation, and continuous improvement
• Partner with the Machine Learning Infrastructure and Data teams to improve tooling, deployment pipelines, and training efficiency
• Lead design and code reviews to promote technical excellence and standardize ML practices across Ads teams
• Diagnose model performance, identify optimization opportunities, and execute experiments that drive measurable results
• Mentor engineers on best practices for ML experimentation, productionization, and scaling
• Work cross-functionally with product, infrastructure, and business teams to align technical innovations with product goals

How Do I Know if the Role is Right For Me?

• You have 7+ years of experience building and deploying ML systems at scale, ideally in AdTech, recommender systems, or search/ranking domains
• You’ve shipped models that directly improved key product or business metrics such as CTR, CVR, or ROI
• You’re fluent in Mandarin Chinese and skilled at collaborating with customers or partners in technical discussions
• You have strong software engineering fundamentals: data structures, algorithms, and system design and proficiency in Python (C++ or Java a plus)
• You’re experienced with modern ML frameworks such as PyTorch, TensorFlow, or JAX
• You’ve worked with distributed data and compute systems like Apache Beam, Dataflow, or Flume
• You understand how to build robust ML pipelines including data versioning, feature engineering, retraining, and model monitoring in production
• You have experience optimizing inference performance on GPUs, TPUs, or similar hardware accelerators
• You thrive in fast-moving, ambiguous environments and can translate complex technical work into measurable business outcomes
• You value collaboration, accountability, and building systems that scale across teams and markets

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!

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.

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.

We are looking for a Manager, Customer Success Engineering (AI & Cloud Support) who is passionate about delivering exceptional support experiences and building high-performing teams.

As a Manager, CSE (AI & Cloud Support) at DigitalOcean, you will operate as a Support Manager leading a team of Customer Success Engineers (CSEs) supporting strategic customers across cloud infrastructure and emerging AI/ML workloads. Reporting to the Senior Manager of Customer Success Engineering, you will own day-to-day support operations, team performance, and customer experience outcomes.

This role is focused on driving operational excellence while building strong technical depth within the team across AI, GPUs, Kubernetes, Databases and core cloud offerings. You will play a key role in ensuring consistent support coverage, developing SMEs, and partnering cross-functionally with Product and Engineering to improve both customer experience and product quality.

The ideal candidate brings a deep understanding of cloud and AI/ML ecosystems, including machine learning operations (MLOps), and enterprise support, combined with a passion for innovation and automation, and a proven ability to lead teams in delivering “white-glove” experiences for strategic customers.

What You’ll Do:

Team Leadership & Development

• Lead, hire, train, mentor and develop a high-performing team of Customer Success Engineers (CSEs), driving accountability, performance, and career growth
• Establish performance metrics (KPIs/SLAs) and conduct regular 1:1s, performance reviews, and career development planning.
• Own end-to-end support operations, including queue management, escalations, and shift planning to ensure consistent 24x7 coverage.
• Drive improvements in key support metrics such as CSAT, response times, resolution times, and overall support quality.
• Build and strengthen technical expertise within the team across core areas such as Kubernetes (DOKS), Databases, Compute, and AI/ML workloads.
  
  

Strategic Customer Support

• Act as the ultimate point of technical escalation for our largest, most strategic enterprise customers across Cloud and AI/ML workloads, stepping in to manage critical incidents and high-severity (Sev1/Sev2) issues.
• Design and implement customized support plans, SLAs, and escalation pathways tailored to the needs of strategic accounts.
• Partner closely with Technical Account Managers (TAMs), Growth Account Managers (GAM) to conduct Executive Business Reviews (EBRs) and ensure customers are maximizing the value of our Cloud and AI/ML products.
• Proactively identify risks and opportunities within strategic accounts to improve customer experience, adoption, and retention.

Technical & Cross-Functional Operations

• Serve as the Voice of the Customer (VoC) to Product and Engineering teams, synthesizing support data to advocate for bug fixes, feature requests, and UX improvements.
• Own and continuously improve escalation protocols between AI/ML Support and CloudOps, Infrastructure Engineering, and Product — including Jira escalation routing, Sev1 bridge management, and post-incident documentation.
•  Own the development and maintenance of SOPs, escalation runbooks, HVC support playbooks, and knowledge base content — treating documentation infrastructure as a core operational lever for team scalability.
• Contribute to the vision for AI and automation within support—building intelligent tooling and driving the team toward an automation-first model to improve efficiency, scalability, and customer experience.
• Foster a culture of continuous learning, ensuring the team stays ahead of evolving cloud technologies, AI/ML frameworks, and industry trends.

Key Metrics:

• Customer Satisfaction (CSAT) for strategic accounts
• Time to Response and Resolution (TTR) for strategic customers
• Tier 1 resolution rate vs. escalation rate
• Time-to-escalation and engineering handoff SLA adherence
• SLA adherence and escalation response times
• Support productivity and quality (QA scores)
• Post-incident documentation completion rate

What You’ll Add to DigitalOcean:

• Experience: 5+ years of experience in Technical Support, Customer Success, or Technical Account Management within B2B SaaS, Cloud, or AI/ML environments ideally including experience supporting AI-native, high-growth companies with 24x7 production dependencies on GPU infrastructure.
• Leadership: 2+ years of people management experience leading technical, customer-facing teams, preferably in a high-growth, post-acquisition, or rapidly scaling environment.
• Technical Domain Expertise: Solid understanding of AI/ML concepts, including Generative AI, Large Language Models (LLMs), natural language processing (NLP), and MLOps. Deep familiarity with GPU infrastructure (NVIDIA H100/H200, bare metal GPU provisioning) and AI inference workloads is strongly preferred.
• Coding/Integration: Proficiency in reading and debugging code (Python preferred) and troubleshooting RESTful APIs and cloud architecture.
• Communication: Excellent verbal and written communication skills, with the ability to translate complex technical or AI concepts for diverse audiences OR to both highly technical engineers and non-technical business executives.
• Problem-Solving: Proven ability to remain calm under pressure and de-escalate high-stakes situations with enterprise clients.

Preferred Qualifications:

• Hands-on experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and AI toolchains (e.g., LangChain, Hugging Face).
• Experience with major cloud platforms (AWS, Google Cloud, Azure) and their native AI/ML services.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related technical field.
• ITIL or equivalent service management certification

Compensation Range: 

• $125,000 - $153,000

*This is a remote role

JR: 2026-7692

#LI-Remote

We want people who are passionate about solving complex cloud infrastructure challenges for our customers.

We are looking for a Solutions Architect with expertise in cloud infrastructure to support the success and retention of DigitalOcean's high-value customers. Reporting to the Manager of Solutions Architecture, you will work directly with Customer Success, Sales, and Support functions to retain and grow DigitalOcean’s largest and fastest growing customers. You will be the technical subject matter expert on DigitalOcean’s portfolio, advising on best practices and guiding customers to the optimal solution to meet their business objectives. You will work closely with other functions within DigitalOcean such as Product, Engineering, and Operations to ensure the needs and insights from the local markets are funneled appropriately back into DigitalOcean's products and services.

This is an amazing growth opportunity for a highly motivated individual to establish and expand our presence within the region. Technical depth, excellent communication skills, and a self-starter mentality are needed.

 What You Will Be Doing: 

As a Senior Solutions Architect II, you will serve as a technical partner to the success and sales teams. You will perform architecture reviews, proof of concepts, demos, uncover customer technical needs, and demonstrate DigitalOcean's value proposition. Working with AEs, GAM and TAM counterparts, you'll help retain large customers and expand their workloads on DigitalOcean.

• Develop deep expertise in the DigitalOcean product portfolio, the evolving cloud landscape, and AI/ML platforms.
• Advocate for customers by providing feedback to product teams, overcoming adoption blockers, and driving new feature development.
• Offer personalized onboarding assistance and guide customers through their cloud journey, resolving technical blockers.
• Design and review architecture tailored to specific business use cases, ensuring optimal solutions for customers.
• Implement and oversee infrastructure management best practices to secure and optimize cloud resources.
• Identify opportunities for cost reduction and performance improvement, helping customers make data-driven cloud optimization decisions.
• Conduct technical consultation sessions, workshops, and training for customers to empower them in managing cloud infrastructure.
• Partner with Growth Account Managers and Customer Success Managers to create success plans that ensure customer retention, expansion, and satisfaction.
• Provide regular presentations articulating product benefits, functionality, and technical solutions.
• Demonstrate strong expertise in AI/ML frameworks like TensorFlow and PyTorch and usage of platforms like Hugging Face, with experience deploying and fine-tuning LLMs and GenAI models.
• Optimize GPU workloads using CUDA or TensorRT and build scalable AI applications like chatbots, inference services or recommendation systems using Kubernetes and NFS.
• Design AI solutions tailored to business needs, manage data pipelines, and integrate databases.
• Liaise with Engineering and Support teams to resolve escalations and growth obstacles in a timely fashion.
• Identify and drive process improvement opportunities and promote technical best practices across the organization.
• Contribute to internal and external documentation, such as "The Navigator’s Guide to DO."
• Build tools to enhance the experience of Premium Support customers and improve platform usability.
• Demonstrate proficiency in DevOps tools like Docker, Terraform, and CI/CD pipelines.
• Leverage expertise in Kubernetes, Managed DBaaS, and the DigitalOcean GenAI Platform.
• Work both independently and collaboratively with a global team of Solutions Architects, Customer Success Managers, and Account Managers.

What We'll Expect From You:

• Proven professional experience with cloud infrastructure, AI/ML platforms, or equivalent education.
• Expertise in AI/ML frameworks (e.g., TensorFlow, PyTorch) and familiarity with platforms like Hugging Face.
• Experience deploying and fine-tuning LLMs (e.g., DeepSeek, Llama, Claude, GPT-4) and GenAI models.
• Deep knowledge of Linux, distributed systems, Kubernetes, NFS, Object Storage, and GPU optimization techniques (e.g., CUDA, TensorRT).
• Hands-on experience leveraging vllm and various quantization methods (e.g., INT4, INT8, and FP8) for efficient model deployment.
• Programming/development experience, particularly in building AI-powered applications (e.g., recommendation systems, chatbots).
• Experience working in a post-sales or technical consultant role with a focus on AI/ML and cloud solutions.
• Knowledge of provisioning, deployment strategies, and tools like Terraform, Kubernetes, and Docker.
• Passionate about customer experience and leveraging AI/ML to solve complex business problems.
• Track record of developing successful technical solutions, including AI/ML use cases, to address customer challenges.
• Ability to balance the demands of multiple stakeholders, define priorities, and set appropriate expectations.
• Strong understanding of AI/ML data pipelines, cloud-native databases, and integration strategies.
• Passionate about technology, open source projects, and applying cutting-edge AI/ML innovations.
• Strong communication skills, with the ability to explain technical AI/ML concepts in clear and concise terms.
• Quickly learn DigitalOcean systems and adapt to rapid changes in cloud and AI/ML trends.
• Fluency in English.
• Highly motivated with a self-starter mentality, ready to tackle AI/ML challenges head-on.

Extra Credit: 

• Cloud certifications are highly desirable (AWS/GCP/Oracle/Azure)
• NVIDIA Certifications around GPU and AI/ML
• Networking: Cisco/Juniper Certifications
• Programming/Scripting: Ruby, Python, Go, Bash
• Source Code: Git
• Automation: Terraform, Ansible, Chef, Puppet, Saltstack
• Virtualization: KVM, Xen
• Databases: MongoDB, MySQL, Redis, PostgreSQL
• Open Source: CoreOS, Docker, Kubernetes (CKA/CKE), Vagrant
• DigitalOcean: API, libraries, services
• Linux: RHCSA/RHCE

Compensation Range: 

• Base: $150,000 - $182,000 / Target OTE: $200,000 - 240,000

*This is a remote role

JR: 2026-7695

#LI-Remote

We are looking for a Strategic Technical Account Manager who is passionate about making an impact, builds genuine relationships with senior stakeholders, and understands how to integrate infrastructure choices into business strategy.

As a Strategic Technical Account Manager (TAM) at DigitalOcean, you will join a dynamic team dedicated to revolutionizing cloud computing and AI. 

What You’ll Do:

Strategic Relationship Management

• Own the technical relationship with DigitalOcean’s highest-value customers, including Fortune 500 companies and global technology leaders.
• Serve as the trusted technical advisor and executive-facing point of contact, building deep, lasting relationships with VP- and SVP-level stakeholders.
• Drive regular technical and strategic alignment sessions (QBRs, EBRs), proactively shaping the customer’s roadmap to maximize the value of DigitalOcean infrastructure.
• Operate as a thought partner, challenging customers to modernize, optimize, and scale AI/ML and GPU workloads using cutting-edge cloud architecture patterns.

Executive Presence & Influence

• Engage with C-level and VP-level contacts with confidence, clarity, and authority.
• Deliver high-impact, boardroom-ready presentations on architecture decisions, cost-performance tradeoffs, and innovation opportunities.
• Navigate complex org structures, ensuring DigitalOcean maintains executive alignment and account control at every level.

Technical Consultation & Innovation Support

• Provide expert guidance on designing and scaling AI/ML, containerized, and GPU-intensive workloads on DigitalOcean.
• Assist customers with architectural planning, workload migration, performance tuning, and incident response.
• Collaborate directly with engineering and product teams to address customer roadblocks and influence the product roadmap based on enterprise needs.

Growth, Retention & Advocacy

• Own technical success across a portfolio of DigitalOcean’s largest and most strategic accounts.
• Identify opportunities for workload expansion, cost optimization, and operational efficiency.
• Act as the voice of the customer, providing structured feedback to influence DigitalOcean's offerings and go-to-market strategies.
  Lead cross-functional account planning with Account Management, Product, and Engineering.

What You’ll Add to DigitalOcean:

Enterprise Customer Experience

• 7+ years supporting enterprise or strategic accounts in a customer-facing technical role (TAM, Solutions Architect, or equivalent).
• Experience working with large-scale organizations like AMD, Intel, or similar, including managing executive-level relationships and navigating matrixed stakeholders.
• Deep understanding of cloud architecture for AI/ML, including GPU orchestration, inference/training pipelines, and model deployment.

Technical Depth

• Proficient in at least one major cloud platform (AWS, GCP, Azure) and familiar with DigitalOcean or other developer-focused platforms.
• Strong hands-on skills with Linux systems, networking, containers (Docker/Kubernetes), and automation (Terraform, Ansible).
  Programming/scripting in Python, Go, or similar—especially relevant to AI/ML and MLOps use cases.
• Understanding of AI/ML infrastructure stacks: PyTorch, TensorFlow, ONNX, Hugging Face, NVIDIA Triton, etc.
• Understanding of AI/ML infrastructure, including frameworks like PyTorch, TensorFlow, and ONNX, with hands-on experience optimizing GPU workloads on both NVIDIA (CUDA, TensorRT) and AMD (ROCm, MIOpen) platforms.
• Comfort with modern DevOps and data stack tools (CI/CD, GitOps, observability, pipelines).

Executive Presence & Communication

• Proven ability to engage with and influence executive decision-makers.
• Exceptional communication skills, including the ability to translate complex technical topics into strategic business impact.
• Comfortable presenting to large audiences, running technical workshops, and defending architectural decisions.

Bonus Points

• Cloud certifications (AWS SA Pro, GCP PCA, Azure Architect) or NVIDIA certifications.
• Experience with high-performance computing, edge AI, or hybrid/multicloud strategies.
• Background in startup or high-growth environments where agility and influence matter.
• Familiarity with DigitalOcean’s developer ecosystem, API, and service portfolio.

Compensation Range: 

•  $174,240 - $217,800

*This is a remote role

#LI-Remote

What We're Looking For

We are seeking a highly skilled Research Engineer to work on optimizing training and inference workloads on compute accelerators and clusters, through the Lightning Thunder compiler and the broader PyTorch Lightning ecosystem. This role sits at the intersection of deep learning research, compiler development, and large-scale system optimization. You’ll be shaping technology that pushes the boundaries of model performance and efficiency, creating foundational software that will impact the entire machine learning ecosystem.

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.

What You'll Do

• Develop performance-oriented model optimizations at multiple levels:
• Graph-level (e.g., operator fusion, kernel scheduling, memory planning)
• Kernel-level (CUDA, Triton, custom operators for specialized hardware)
• System-level (distributed training across GPUs/TPUs, inference serving at scale)
• Advance the Thunder compiler by building optimization passes, graph transformations, and integration hooks to accelerate training and inference workloads.
• Work across the software stack to ensure optimizations are accessible to end users through clean APIs, automated tooling, and seamless integration with PyTorch Lightning.
  Design and implement profiling and debugging tools to analyze model execution, identify bottlenecks, and guide optimization strategies.
• Collaborate with hardware vendors and ecosystem partners to ensure Thunder runs efficiently across diverse backends (NVIDIA, AMD, TPU, specialized accelerators).
• Contribute to open-source projects by developing new features, improving documentation, and supporting community adoption.
• Engage with researchers and engineers in the community, providing guidance on performance tuning and advocating for Thunder as the go-to optimization layer in ML workflows.
• Work cross-functionally with Lightning’s product and engineering teams to ensure compiler and optimization improvements align with the broader product vision.

What You’ll Need

• Strong expertise with deep learning frameworks such as PyTorch
• Hands-on experience with model optimization techniques, including graph-level optimizations, quantization, pruning, mixed precision, or memory-efficient training.
• Knowledge of distributed systems and parallelism strategies (data/model/pipeline parallelism, checkpointing, elastic scaling).
• Familiarity with software engineering practices: designing APIs, building robust tooling, testing, CI/CD for performance-sensitive systems.
• Excellent collaboration and communication skills, with the ability to partner across research, engineering, and external contributors.
• Bachelor’s degree in Computer Science, Engineering, or a related field.

Nice-to-Haves

• Experience with CUDA, Triton, or other GPU programming models for developing custom kernels.
• Deep understanding of deep learning compiler internals (IR design, operator fusion, scheduling, optimization passes) or proven work in performance-critical software.
• Proven track record contributing to open-source projects in ML, HPC, or compiler domains.
• Advanced degree (Master’s or PhD) in machine learning, compilers, or systems highly preferred.

Compensation

What We're Looking For

We are looking for a Senior Application Security Engineer to help secure our AI, machine learning, and inference platforms. This is a hands on technical role focused on building security into modern AI infrastructure, inference systems, and developer platforms.

You will work closely with platform engineers, ML engineers, and infrastructure teams to identify risks, design secure architectures, and build security tooling that enables engineers to move quickly and safely.

This role is execution focused. You will drive technical implementation, perform deep security reviews, and help build out our application security capabilities alongside the CISO and engineering leadership.

This role can be based out of one of our office hubs (San Francisco or Seattle) with in-office requirements of at least 2 days per week, plus occasional team/company offsites. We are not able to offer visa sponsorship for this position at this time.

What You’ll Do

Secure AI and Machine Learning Systems

• Perform threat modeling across AI platforms, inference services, and ML pipelines
• Identify risks such as prompt injection, model extraction, adversarial inputs, and data leakage
• Review model serving architectures and inference pipelines
• Partner with ML engineers to secure training, fine tuning, and deployment workflows
• Help design isolation and security controls for multi tenant AI workloads

Application Security Engineering

• Perform architecture and design security reviews
• Conduct targeted code reviews for high risk components
• Identify security gaps in APIs, micro-services, and distributed systems
• Build secure patterns for authentication, authorization, and service to service communication
• Help engineering teams implement secure defaults and guardrails

Inference Platform Security

• Secure customer facing inference APIs and services
• Protect against abuse, model extraction, and adversarial behavior
• Design rate limiting, isolation, and workload protection controls
• Build monitoring and detection for anomalous inference behavior

AI Supply Chain and Model Security

• Evaluate open source models and dependencies
• Secure model artifacts and distribution pipelines
• Implement integrity validation and provenance controls
• Help secure container images and runtime environments

Security Automation and Tooling

• Build security automation for AI and application pipelines
• Integrate security scanning into CI/CD workflows
• Develop tooling to help engineers detect and fix issues early
• Improve developer experience with security guardrails

What You'll Need

Required Experience

• Strong background in application security engineering
• Experience performing threat modeling and architecture reviews
• Experience securing APIs and distributed systems
• Experience working in cloud environments such as AWS, GCP, or Azure
• Experience with containers and Kubernetes
• Strong scripting or programming skills such as Python, Go, or similar
• Experience working closely with engineering teams to implement security improvements

AI and Machine Learning Experience

• Experience securing ML pipelines, inference systems, or data platforms
• Familiarity with risks such as prompt injection, model extraction, and adversarial inputs
• Experience reviewing model serving architectures
• Understanding of training data security and data leakage risks

It's a Strong Plus If You Have

• Red team or offensive security experience
• Experience crafting payloads and evaluating CVEs for exploitability in diverse environments
• Experience with GPU infrastructure or high performance computing
• Experience with Hugging Face, PyTorch, TensorFlow, or similar frameworks
• Experience with LLM systems, RAG pipelines, or agent frameworks
• Experience building security automation pipelines
• Experience securing multi tenant infrastructure

What Success Looks Like

• Security is embedded into AI platform architecture early
• Engineering teams ship quickly with secure defaults
• Inference platforms are resilient against abuse and extraction
• Model pipelines are secure and auditable
• Security tooling scales with engineering growth

Why This Role Matters

This role sits at the intersection of application security, AI infrastructure, and developer platforms. You will help define how we secure modern AI systems while enabling engineers to move quickly and safely.

You will work closely with engineering leadership and the CISO to build practical, scalable security capabilities that support rapid innovation in AI and machine learning.

Compensation

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators and problem solvers to help us create it.

Who you are

Metropolis is seeking a Senior Manager of Machine Learning Engineering within the Advanced Technologies Group to lead the technical vision and execution of our foundational systems that power our next generation of AI. You will oversee 4 critical pillars within the Machine Learning org:data engineering, annotation pipelines, ML Infrastructure and Deployment of Agentic AI solutions. You are a hands-on, senior technical leader with a broad dynamic range, capable of providing high-level strategic direction while remaining technically proficient enough to dive into the weeds with your team. Your mission is to transition state-of-art models into robust, autonomous production systems that automate complex enterprise workflows.You will partner closely with internal engineering teams and external vendors to build the scalable tools and data pipelines that define the future of recognition economy.

What you'll do

• Build and maintain scalable, compliant and auditable data infrastructure to serve computer vision and AI pricing use cases 
• Build scalable data engineering pipelines and automated annotation workflows (LLM-in-the-loop) to reduce reliance on manual labeling and accelerate model iteration
• Own the MLOps lifecycle, including distributed training infrastructure, model registries, and low-latency inference services. Ensure high availability and observability for all deployed models
• Define technical direction, lead and grow a high-performance team of data and ML infrastructure engineers to influence impactful business outcomes
• Develop foundational systems to productionize agentic AI, Large Language Models (LLMs) and Vision Language Models (VLMs) solutions for workflow automation to enhance our products
• Enable Metropolis’s move into personalization and targeted advertisement through innovative ML data pipelines and feature stores
• Collaborate with external vendors and annotation platform providers to ensure high-quality data for production models
• Partner with other ML leaders (Growth , Edge deployment) and cross-functional leaders in Hardware, Platform, and Product engineering to align development roadmaps

What we're looking for

• 10+ years of professional experience in data and machine learning engineering with proven expertise in building enterprise-scale, auditable ETL pipelines and data governance mechanisms
• 5+ years of experience in leadership and management, ideally having managed other managers
• MS or PhD in computer science and/or a quantitative discipline
• Strong experience in distributed data processing like Apache Spark, Kafka, Cloud native data storage and processing services
• 1+ years experience building data /eval pipelines and deploying agentic AI solutions (LLMs and/or VLMs)
• Experience managing technical programs, defining milestones, and communicating progress to diverse audiences
• Familiarity with deep learning frameworks such as TensorFlow or PyTorch
• Strong proficiency with SQL and Python
• Engage effectively with external data providers and vendors
• Familiarity with computer vision systems and models (e.g. object detection, tracking, segmentation)

While not required, these are a plus:

• Manage large scale datasets and database tools for data processing
• Deploy ML services to the cloud with a focus on scalability and reliability
• Operate in innovative, high-growth environments

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $200,000.00 USD to $250,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-AR1 #LI-Onsite

The Community You Will Join:

At Airbnb, we believe technology has the power to bring people together — and our engineers are the ones building it. Our Engineering org is a diverse, fast-moving group of teams working across Payments, Trust, Marketing, Relevance & Personalization, and more. Together, we're tackling some of the hardest problems in tech: search relevance at global scale, fraud prevention, seamless payments, and fueling growth — all while delivering a product experience that feels effortless and beautiful. We're also at the forefront of integrating AI and machine learning into our products — from personalized search experiences to intelligent trust and safety systems — and we're looking for curious engineers who are excited to grow alongside this technology.

If you're energized by engineering that creates real-world human connection — and by the idea that your code will be experienced by millions of people around the world — you'll feel right at home here.

The Difference You Will Make:

As a Software Engineer (New Grad) at Airbnb, you’ll play a vital role in building, supporting, and refining the products and systems that make Airbnb’s mission possible. Your work will directly contribute to high-quality, reliable experiences for our global community—whether you’re fixing bugs, launching well-defined features, or enhancing existing components. You'll also have the opportunity to contribute to AI-powered features, applying foundational knowledge of machine learning concepts and modern AI tools to build smarter, more personalized experiences for our hosts and guests. By clearly communicating challenges and collaborating with teammates across functions, you’ll help drive projects forward with transparency and trust.

You’ll foster a sense of belonging by actively seeking feedback, sharing your own learnings, and supporting the onboarding of new team members. You’ll help uphold Airbnb’s commitment to excellence by following best practices, delivering tasks autonomously, and continually improving your technical skills. Your curiosity, empathy, and commitment to candid communication will empower you to make a meaningful impact—on projects, teammates, and Airbnb’s inclusive culture.

A Typical Day: 

• Attend team syncs to discuss priorities, share progress, and surface any blockers with transparency.
• Dive into coding—fixing bugs, developing features, or refining APIs and components—while applying best practices for code quality, error handling, and testability. Leverage AI-assisted development tools (e.g., Claude Code or similar) to accelerate your workflow and improve code quality.
• Participate in design or code reviews, ask clarifying questions, and apply feedback to improve your work. Work closely with cross-functional partners like product managers and designers to ensure your tasks align clearly with broader goals.
• Dedicate time to expanding your technical knowledge through documentation, mentorship, or internal knowledge-sharing sessions. This includes staying current on AI/ML developments relevant to your team's domain — whether that's recommendation systems, natural language understanding, or AI safety practices. Seek guidance from managers or tech leads when tackling unfamiliar problems.
• Contribute to team activities, such as onboarding new hires (e.g., being an onboarding buddy), sharing observations from the hiring process, or joining in cultural events focused on diversity, inclusion, and innovation.
• Share updates on your progress and next steps, highlighting challenges or learnings. 

Your Expertise:

This role is designed for recent graduates (Bachelor's or Master's) with less than 1 year of full-time professional experience who are ready to grow fast and make an impact.

• Strong foundation in Computer Science fundamentals — data structures, algorithms, design patterns, and systems thinking
• Proficiency in one or more of: Java, Scala, Ruby, Ruby on Rails, C++, SQL, HTML/CSS, JavaScript, Objective-C, Swift (iOS), or Kotlin (Android)
• Foundational awareness of AI/ML concepts — such as supervised learning, model evaluation, or working with APIs backed by large language models (LLMs) — gained through coursework, personal projects, or internships
• Familiarity with Python and common AI/ML libraries (e.g., NumPy, scikit-learn, or PyTorch) is a plus, as is experience integrating cloud-based AI services or LLM APIs
• An understanding of responsible AI principles — including fairness, privacy, and safety — and a curiosity about how these apply to real-world product development
• Bonus points for leadership experience, community involvement, or teaching/mentoring — we love engineers who invest in others

Your Location:

Preference for candidates based in San Francisco, California or Seattle, Washington with the ability to commute to the office three days per week. Additional in-person attendance for team meetings or offsites may be required as needed. Domestic Relocation support will be provided for candidates open to relocating.

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process. 

We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.

As a machine learning intern in our Advance Technology Group at Pinterest, you will be exposed to a full spectrum of ML product development. The team focuses on developing cutting-edge technologies for Pinterest’s visual understanding modules and recommender systems.  You'll conduct research that can be applied across Pinterest engineering teams and engage in external collaborations and mentoring, while also having opportunities to deploy features to hundreds of millions of users or conduct research applicable for paper submissions. We offer a 12-week fall internship program remotely or in our San Francisco, Palo Alto, Seattle, or New York offices.

Note to applicants:

By applying to this role, you will be considered for multiple intern roles open across our various ML teams. Please only apply once within the USA or Canada as multiple applications may delay our recruitment process.

Internships are 12 weeks paid from September 21 - December 11, 2026. Depending on the team, our fall internships will be located either remote or hybrid in San Francisco, Palo Alto, New York or Seattle offices.

What you’ll do:

• Develop and launch new user features using unique internal datasets and ML techniques, especially in recommendation systems, computer vision, representation learning, generative AI, and responsible AI.
• Gain hands-on experience with production ML systems, including algorithmic research, infrastructure, data engineering, training, inference, and product, to deliver innovative solutions. You will be exposed to full-stack production ML systems.
• Leverage frontier AI tools and agents to accelerate engineering implementation, including prototyping and experimentation work.
• Validate AI-generated outputs through testing, code review, and critical thinking, ensuring solutions are accurate, maintainable, secure, and aligned with team standards.
• Use AI to better understand unfamiliar code, investigate bugs, and summarize technical context or documentation.
• Contribute in cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems
• Write clean, efficient, and sustainable code
• Take proactive ownership over the completion and quality of your tasks and project with minimal guidance from your mentor, manager, and peers

What we’re looking for:

• This role will be on our Visual Search or Applied Science teams. We are looking for candidates with experience in Computer Vision, Visual Search, User Understanding, Recommendation Systems, Reinforcement Learning, ML efficiency optimization, Generative AI, and LLMs. 
• Ability to legally work full time (40 hours/week) from September-December 2026
• Working towards a PhD degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field
• Mastery of at least one systems language (Java, C++, Python) and one ML framework (Tensorflow, Pytorch, MLFlow)
• Proficiency with AI-native engineering, including the design of agent-friendly codebases.
• High degree of autonomy in learning new agent-first development tools.
• Strong critical thinking when working with AI-generated suggestions, with a clear approach to validating correctness, performance, security, and maintainability.
• Comfort iterating on prompts, refining workflows, and adapting AI-assisted approaches based on the problem, context, and constraints.
• Experience in research and in solving analytical problems
• Strong communicator and team player. Being able to find solutions for open-ended problems.

Preferred Qualifications:

• • Publications in machine learning, AI, data science, data analytics, statistics, or related technical fields
  • Strong passion for research and for answering hard questions with research
  • Passion for applied ML and the Pinterest product

Why Intern at Pinterest?

• Meaningful Work: Contribute to projects that impact millions of users worldwide.
• Mentorship: Learn from and be guided by experienced engineers and researchers in the field.
• Growth and Development: Participate in professional development workshops and networking events to build your skills and connections.

In-Office Requirement Statement:

• We let the type of work you do guide the collaboration style. That means we’re not always working in an office, but we continue to gather for key moments of collaboration and connection
• This role may require you to be located near an office for in-person collaboration, and therefore may need to be located a commutable distance from one of our Pinterest offices.

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

US based applicants only

The salary for this position is $12,100 monthly.

#LI-HYBRID
#LI-EB1

As a machine learning intern in our Advance Technology Group at Pinterest, you will be exposed to a full spectrum of ML product development. The team focuses on developing cutting-edge technologies for Pinterest’s visual understanding modules and recommender systems.  You'll conduct research that can be applied across Pinterest engineering teams and engage in external collaborations and mentoring, while also having opportunities to deploy features to hundreds of millions of users or conduct research applicable for paper submissions. We offer a 12-week fall internship program remotely or in our San Francisco, Palo Alto, Seattle, or New York offices.

Note to applicants:

By applying to this role, you will be considered for multiple intern roles open across our various ML teams. Please only apply once within the USA or Canada as multiple applications may delay our recruitment process.

Internships are 12 weeks paid from September 21 - December 11, 2026. Depending on the team, our fall internships will be located either remote or hybrid in San Francisco, Palo Alto, New York or Seattle offices.

What you’ll do:

• Develop and launch new user features using unique internal datasets and ML techniques, especially in computer vision, generative AI, and responsible AI.
• Gain hands-on experience with production ML systems, including algorithmic research, infrastructure, data engineering, training, inference, and product, to deliver innovative solutions. You will be exposed to full-stack production ML systems.
• Leverage frontier AI tools and agents to accelerate engineering implementation, including prototyping and experimentation work.
• Validate AI-generated outputs through testing, code review, and critical thinking, ensuring solutions are accurate, maintainable, secure, and aligned with team standards.
• Use AI to better understand unfamiliar code, investigate bugs, and summarize technical context or documentation.
• Contribute in cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems
• Write clean, efficient, and sustainable code
• Take proactive ownership over the completion and quality of your tasks and project with minimal guidance from your mentor, manager, and peers

What we’re looking for:

• This role will be on our Visual Search team. We are looking for candidates with experience in Computer Vision, Visual Search, User Understanding, Generative AI, and LLMs. 
• Ability to legally work full time (40 hours/week) from September-December 2026
• Working towards a Master's degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field
• Mastery of at least one systems language (Java, C++, Python) and one ML framework (Tensorflow, Pytorch, MLFlow)
• Proficiency with AI-native engineering, including the design of agent-friendly codebases.
• High degree of autonomy in learning new agent-first development tools.
• Strong critical thinking when working with AI-generated suggestions, with a clear approach to validating correctness, performance, security, and maintainability.
• Comfort iterating on prompts, refining workflows, and adapting AI-assisted approaches based on the problem, context, and constraints.
• Experience in research and in solving analytical problems
• Strong communicator and team player. Being able to find solutions for open-ended problems.

Preferred Qualifications:

• • Publications in machine learning, AI, data science, data analytics, statistics, or related technical fields
  • Strong passion for research and for answering hard questions with research
  • Passion for applied ML and the Pinterest product

Why Intern at Pinterest?

• Meaningful Work: Contribute to projects that impact millions of users worldwide.
• Mentorship: Learn from and be guided by experienced engineers and researchers in the field.
• Growth and Development: Participate in professional development workshops and networking events to build your skills and connections.

In-Office Requirement Statement:

• We let the type of work you do guide the collaboration style. That means we’re not always working in an office, but we continue to gather for key moments of collaboration and connection
• This role may require you to be located near an office for in-person collaboration, and therefore may need to be located a commutable distance from one of our Pinterest offices.

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

US based applicants only

The salary for this position is $11,00 monthly.

#LI-HYBRID
#LI-EB1

ABOUT THE ROLE:

As a multimodal engineer on the Imagine Model Team, you will develop cutting-edge AI experiences beyond text, with a strong focus on enabling high-fidelity understanding and generation across image and video modalities, while also incorporating audio where it enhances visual content (e.g., synchronized audio for video). Responsibilities span data curation, modeling, training, inference serving, and product integration, covering both pretraining and post-training phases. You will collaborate closely with product teams to push model frontiers and deliver exceptional end-to-end user experiences.

RESPONSIBILITIES:

• Create and drive engineering agendas to advance multimodal capabilities, with emphasis on image and video generation, editing, understanding, controllable/long-horizon synthesis, agentic planning, RL training, and world simulation (including audio integration for richer video experiences).
• Improve data quality through annotation, filtering, augmentation, synthetic generation, captioning, and in-depth data studies, particularly for visual and audio data. 
• Design evaluation frameworks, metrics, benchmarks, evals, and reward models tailored to image/video/audio quality and coherence.
• Implement efficient algorithms for state-of-the-art model performance, including real-time inference, distillation, and scalable serving for visual content.
• Develop scalable data collection and processing pipelines for multimodal (primarily image/video-focused) datasets.
• Collaborate cross-functionally to integrate AI solutions into production and rapidly iterate based on user feedback.

BASIC QUALIFICATIONS:

• Track record in leading studies that significantly improve neural network capabilities and performance through better data or modeling.
• Experience in data-driven experiment designs, systematic analysis, and iterative model debugging.
• Experience developing or working with large-scale distributed machine learning systems.
• Ability to deliver optimal end-to-end user experiences.
• Hands-on contributor with initiative, excellence, strong work ethic, prioritization skills, and excellent communication.

PREFERRED SKILLS AND EXPERIENCE:

• Experience in SFT, RL, evals, human/synthetic data collection, or agentic systems.
• Proficiency in Python, JAX/XLA, PyTorch, Rust/C++, Spark, Ray, and related large-scale frameworks.
• Domain expertise in multimodal applications such as graphics engines, rendering techniques, image/video understanding and generation, world models, real-time simulation, or controllable/long-horizon visual content creation (audio/speech processing or music/audio generation experience is a plus where it supports video).
• Experience with agentic RL training, controllable/long-horizon generation, or multimodal agents that reason and act across modalities (especially in visual domains).

COMPENSATION AND BENEFITS:

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

About impact.com
impact.com is the world’s leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products - Performance (affiliate), Creator (influencer), and Advocate (customer referral) - unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,000 global brands - including Walmart, Uber, Shopify, Lenovo, L’Oréal, and Fanatics - rely on impact.com to power more than 350,000 partnerships that deliver measurable business results.

Your Role at impact.com:

We're seeking a Senior Data Scientist to serve as an embedded Data Scientist within our Programmatic Experience Group. You'll own the design and deployment of machine learning models that optimize yield, pricing, and inventory allocation at scale — sitting at the intersection of data science, platform engineering, and marketplace economics.

This is a high-craft, high-ownership individual contributor role. You'll work end-to-end: architecting the data pipelines that feed your models, engineering the features that drive performance, and deploying real-time inference systems that make decisions at speed. Your work directly determines how effectively Impact's programmatic marketplace balances advertiser performance with publisher monetization — making this one of the highest-leverage technical roles in the business.

You'll collaborate closely with Product, Data Science, and Programmatic Delivery Engine Engineering, but you operate with significant autonomy. You're expected to bring both the modeling rigor of a data scientist and the production instincts of an ML engineer — and to be genuinely excited about both.

What You'll Do:

Yield Optimization & Pricing Models

• Design and deploy ML models that optimize auction pricing, bid shading, floor price setting, and yield across Impact's programmatic inventory.
• Build and iterate on real-time pricing algorithms that balance short-term revenue efficiency with long-term publisher and advertiser health.
• Develop and maintain feedback loops that allow pricing models to adapt to shifting market conditions, inventory mix, and demand patterns.
• Quantify the revenue impact of pricing model improvements; communicate tradeoffs between yield maximization, fill rate, and partner ROI to stakeholders.

Inventory Allocation & Supply Optimization

• Own ML-driven inventory allocation logic: routing, pacing, and matching supply to demand across partner segments, deal types, and campaign objectives.
• Build models that forecast inventory availability, demand curves, and clearing prices to support proactive allocation decisions.
• Identify and address inefficiencies in inventory utilization — including unsold inventory, suboptimal deal matching, and allocation imbalances across the publisher base.

Data Architecture & Feature Engineering

• Design and own the data infrastructure that feeds programmatic models: event pipelines, feature stores, training datasets, and real-time feature serving.
• Engineer high-signal features from auction logs, bid stream data, user signals, contextual attributes, and historical performance — at the scale of programmatic data volumes.
• Build robust data pipelines with production-grade standards: reliability, observability, versioning, and efficient reprocessing.

Real-Time Inference & Production ML

• Deploy models to production real-time inference environments; own latency, reliability, and throughput requirements for auction-time decision-making.
• Build monitoring systems that track model performance, data drift, and system health in production; define alerting thresholds and retraining triggers.
• Partner with MLOps and Platform Engineering to ensure scalable, low-latency serving infrastructure meets SLOs under high-volume auction traffic.
• Own the full model lifecycle: training, evaluation, deployment, A/B testing, and iteration.

Experimentation & Performance Measurement

• Design and execute rigorous A/B and holdout experiments to measure the causal impact of model changes on yield, fill rate, advertiser performance, and publisher revenue.
• Build evaluation frameworks that go beyond offline metrics — validating model behavior in live auction environments where feedback signals are delayed or noisy.
• Translate experimental results into clear business narratives; present findings and recommendations to Product and business stakeholders.

Self-Learning Systems & Feedback Loops

• Research and implement adaptive, self-learning components within the programmatic stack — including contextual bandits, reinforcement learning signals, and online learning approaches where appropriate.
• Design feedback mechanisms that close the loop between auction outcomes, model updates, and system behavior; reduce reliance on manual tuning and rule-based overrides.
• Stay current with advances in programmatic ML, auction theory, and online optimization; evaluate applicability to Impact's specific marketplace dynamics.

Cross-Functional Collaboration

• Serve as the primary ML technical partner for the Rubicon product and engineering teams; translate business requirements into modeling approaches and communicate technical tradeoffs clearly.
• Collaborate with Data Science peers on shared infrastructure, modeling standards, and cross-domain feature reuse.
• Document models, architectures, and experimental findings to a standard that enables review, replication, and knowledge transfer across teams.

What You Bring:

Required

• Experience: 5+ years in data science, ML engineering, or quantitative research, with at least 2+ years building and deploying ML models in programmatic advertising, ad tech, marketplace optimization, or a closely related domain (e.g., real-time bidding, dynamic pricing, auction systems).
• Programmatic & marketplace depth: Demonstrated understanding of programmatic auction mechanics (RTB, header bidding, floor pricing, deal types, bid shading) and how ML can be applied to optimize outcomes across the supply-demand stack.
• Production ML engineering: Proven ability to take models from prototype to production independently — including real-time inference, monitoring, retraining pipelines, and SLO ownership.
• Data architecture: Experience designing and building data pipelines, feature stores, and training infrastructure for high-volume, low-latency ML systems.
• Technical skills:
• Strong Python and SQL; proficiency with ML libraries (scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow) and large-scale data tools (Spark, Kafka, or equivalent streaming/batch frameworks).
• Experience with real-time feature serving and low-latency model deployment (REST APIs, gRPC, or streaming inference).
• Familiarity with production ML workflows: model versioning, drift monitoring, A/B testing, evaluation, and retraining.
• Experience processing and modeling at programmatic data scale: high-cardinality auction logs, bid stream data, impression and click events.
• Experimentation rigor: Strong grasp of causal inference and experiment design in online, delayed-feedback environments (auction holdouts, switchback tests, variance reduction techniques).
• Communication: Ability to explain complex modeling decisions and tradeoffs to Product and business stakeholders; comfortable presenting in cross-functional forums.
• Education: Bachelor's in a quantitative field (CS, Statistics, Math, Engineering, Economics, or similar); Master's/PhD preferred.

Preferred / Nice to Have

• Direct experience with SSP, DSP, or exchange-side yield optimization — particularly floor price optimization, bid landscape modeling, or deal matching algorithms.
• Familiarity with auction theory (first-price vs. second-price dynamics, optimal reserve pricing, revenue equivalence) and its practical implications for programmatic ML.
• Experience with contextual bandits, multi-armed bandits, or reinforcement learning applied to real-time decisioning problems.
• Knowledge of online learning and adaptive algorithms in production environments with non-stationary data distributions.
• Familiarity with privacy-preserving ML techniques relevant to programmatic (differential privacy, federated learning, cookieless attribution modeling).
• Experience with GCP tools (BigQuery, Vertex AI, Dataflow, Pub/Sub) and/or Databricks/Spark for large-scale event processing and model training.
• Exposure to supply forecasting, inventory management, or capacity planning in programmatic or marketplace contexts.
• Familiarity with Impact's affiliate and partnership ecosystem, or prior experience at the intersection of performance marketing and programmatic delivery.

What Sets You Apart

• Marketplace intuition. You understand programmatic auctions not just as an engineer but as an economist — you think about incentive structures, equilibrium dynamics, and how model decisions ripple through the supply-demand stack.
• Full-stack ML ownership. You're as comfortable designing a feature store schema as you are tuning a gradient boosting model or debugging a latency spike in production. You own the whole chain.
• Feedback loop thinking. You don't just deploy models — you design the systems that make them smarter over time. You think about how today's decisions become tomorrow's training signal.
• Rigor under real-world constraints. You know how to run clean experiments in environments where feedback is delayed, data is noisy, and business pressures create tradeoffs. You don't let imperfect conditions become an excuse for imprecise thinking.
• Pragmatic delivery. You ship. You balance the perfect with the production-ready, iterate fast, and know when an MVP outperforms a six-month research project.
• Collaborative depth. You build genuine technical trust with engineering and product partners — not just by having good ideas, but by following through, communicating clearly, and making the integration easy.

Salary Range: $165,000 - $185,000 per year, plus an additional 5% variable annual bonus contingent on Company performance and eligible to receive a Restricted Stock Unit (RSU) grant.

*This is the pay range the Company believes is equitable for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time.

Benefits and Perks: 

At impact.com, we believe that when you’re happy and fulfilled, you do your best work. That’s why we’ve built a benefits package that supports your well-being, growth, and work-life balance.

• Medical, Dental, and Vision insurance
• Office-only catered lunch every Thursday, a healthy snack bar, and great coffee to keep you fueled 
• Flexible spending accounts and 401(k)
• Flexible Working: Our Responsible PTO policy means you can take the time off you need to rest and recharge. We're committed to a positive work-life balance and provide a flexible environment that allows you to be happy and fulfilled in both your career and your personal life.
• Health and Wellness: Your well-being is a priority. Our mental health and wellness benefit includes up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage. We also offer a monthly gym reimbursement policy to support your physical health.
• A Stake in Our Growth: We offer Restricted Stock Units (RSUs) as part of our total compensation, giving you a stake in the company's growth with a 3-year vesting schedule, pending Board approval.
• Investing in Your Growth: We’re committed to your continuous learning. Take advantage of our free Coursera subscription and our PXA courses.
• Parental Support: We offer a generous parental leave policy, 26 weeks of fully paid leave for the primary caregiver and 13 weeks fully paid leave for the secondary caregiver.
• Technology Financial Support: We provide a technology stipend to help you set up your home office and a monthly allowance to cover your internet expenses. 

impact.com is proud to be an equal-opportunity workplace. All employees and applicants for employment shall be given fair treatment and equal employment opportunity regardless of their race, ethnicity or ancestry, color or caste, religion or belief, age, sex (including gender identity, gender reassignment, sexual orientation, pregnancy/maternity), national origin, weight, neurodivergence, disability, marital and civil partnership status, caregiving status, veteran status, genetic information, political affiliation, or other prohibited non-merit factors.

#LI_Seattle

Your Impact

We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a key member of our research and development efforts, you will play a crucial role in advancing the state-of-the-art in Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), Computer Vision and GenAI technologies for law enforcement and beyond. You will collaborate with cross-functional teams to design, develop, and deploy cutting-edge LLM, MLLM, CV models and algorithms and solutions that enable intelligent reasoning, perception and understanding of multimodal data.

What You’ll Do
Location: any cities with Axon Engineering Hub in US, Vietnam, EU (see https://www.axon.com/company)

• US: Seattle, Boston, Scottsdale

Responsibilities

• Own one or more key technical areas across LLM, MLLM, CV product portfolio.
• Provide technical leadership to junior scientists, guiding the transition of R&D concepts into impactful Axon product feature.
• Research and develop cutting-edge techniques in LLM, MLLMs, GenAI, and Computer Vision across cloud, devices and sensors based data sources.
• Design and implement efficient and scalable MLLM models for inference and analysis of multimodal data.
• Explore novel approaches to address challenges in NLP, NLU, Object Detection, Object Recognition, Object Tracking, Segmentation, and Scene Understanding.
• Optimize AI models, algorithms for performance, memory footprint, and energy efficiency to meet the requirements of resource-constrained devices.
• Join force with MLEs or firmware or hardware engineers to leverage hardware accelerators and optimize algorithms for specific hardware architectures.
• Evaluate the performance of LLM, MLLM, CV models using real-world datasets and design experiments to validate their effectiveness.
• Stay up-to-date with the latest research trends and advancements in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant findings into our projects.
• Contribute to patent disclosures, academic publications, and technical documentation to share insights and findings with the broader community.
• Experience coach and mentor junior scientists.

What You Bring

• PhD and with +5 years for ML Scientist, +8 years for Sr. ML Scientist, +10 years for Principal ML Scientist experience in Computer Science or a related field with a focus on LLM, MLLMs, Computer Vision, GenAI.
• Proven track record of research excellence in LLM, MLLM, Computer Vision, Robotics Perception, GenAI, demonstrated through publications in top-tier conferences or journals.
• Strong proficiency in programming languages such as Python, C/C++, experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras and experience with ROS or robotic operational system.
• Drive one or more phases of the ML development lifecycle: shape datasets, investigate modeling approaches and architectures, train/evaluate/tune models and implement the end-to-end training pipeline.
• Leverage state-of-the-art research to deliver high quality models enabling multiple AI projects at scale.
• Contribute back to the research community via academic publications, tech blogs, open-source code and contributing to internal/external AI challenges
• Experience in developing computer vision algorithms for resource-constrained devices such as mobile phones, IoT devices, or embedded systems is highly desirable.
• Excellent problem-solving skills, analytical thinking, and the ability to work independently as well as collaboratively in a team environment.
• Strong communication skills and the ability to effectively present complex technical concepts to both technical and non-technical audiences.

Benefits that Benefit You

• Competitive salary and 401k with employer match
• Discretionary paid time off
• Paid parental leave for all
• Medical, Dental, Vision plans
• Fitness Programs
• Emotional & Mental Wellness support
• Learning & Development programs
• And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work

Location: This role is based out of our Seattle, WA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesday through Friday, with flexibility to work remotely on Mondays. We believe connection fuels innovation, and our in-office culture is designed to support meaningful teamwork and mentorship.

Your Impact

We are seeking multiple highly skilled Full-Stack members of Technical Staff (MTS) to join our CoreAI organization, driving end-to-end development of AI systems across Cloud, Edge Devices, Mission Critical and Robotics platforms.

This role goes beyond pure research. You will operate across the full stack, from data, models, and infrastructure to system integration and production deployment, to deliver scalable, real-world AI solutions. You will work on cutting-edge applications spanning computer vision, NLU, multimodal AI (MLLMs), and GenAI, enabling intelligent perception, reasoning, and action in mission-critical environments.

As a senior technical leader, you will partner closely with research scientists, machine learning engineers, hardware, firmware, and product teams to translate advanced algorithms into robust, production-ready systems that operate reliably at scale.

Why This Role

You will have the opportunity to own and shape end-to-end AI systems that operate in real-world environments, bridging the gap between cutting-edge research and impactful production deployment. This role is ideal for engineers who thrive at the intersection of AI, systems, and product, and want to build scalable, high-impact solutions across cloud and edge.

What You’ll Do
Location: any cities with Axon Engineering Hub in US, Vietnam, EU (see https://www.axon.com/company)

• US: Seattle, Boston, Scottsdale

Responsibilities

• Own end-to-end system development across data pipelines, model development, evaluation, and deployment for AI-powered products.
• Design and build scalable, production-grade systems for real-time perception, multimodal understanding, and decision-making.
• Develop and deploy models across cloud and edge environments, including resource-constrained devices.
• Architect and optimize full-stack AI pipelines, including:
• Translate research advances in computer vision, NLU, GenAI, and multimodal LLMs into production systems.
• Collaborate cross-functionally with MLE, hardware, firmware, and product teams to integrate AI into real-world systems.
• Optimize solutions for hardware-specific acceleration (GPU, NPU, DSP) and edge deployment.
• Define and drive evaluation frameworks and metrics to ensure system performance, reliability, and safety.
• Lead technical direction for complex, ambiguous problems and influence system architecture across teams.
• Contribute to technical design docs, internal knowledge sharing, and long-term platform strategy.

Basic Qualifications

• Master’s, or PhD in Computer Science, Electrical Engineering, or related field
• 8+ years (L8) or 10+ years (L9) of industry experience building production systems
• Strong programming skills in Python/C++ and experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
• Proven experience delivering end-to-end systems from concept to production
• Deep expertise in one or more areas:
• Experience building and scaling distributed systems or cloud-based ML pipelines
• Experience optimizing models for latency, cost, and deployment constraints

Preferred Qualifications

• Experience deploying AI both on Cloud (AWS, AzureML), edge devices (e.g., mobile, embedded systems, robotics platforms on Qualcomm, NVIDIA, Intel)
• Familiarity with hardware acceleration frameworks (TensorRT, ONNX, SNPE, etc.)
• Experience with real-time systems and streaming data pipelines
• Knowledge of multimodal data processing (vision, audio, text, sensor fusion)
• Experience with AWS or other cloud platforms for large-scale inference and training
• Strong system design and architecture skills across cloud ↔ edge environments
• Track record of technical leadership, mentoring, and driving cross-team initiatives
• Experience in privacy-preserving AI, security, or safety-critical systems

Benefits that Benefit You

• Competitive salary and 401k with employer match
• Discretionary paid time off
• Paid parental leave for all
• Medical, Dental, Vision plans
• Fitness Programs
• Emotional & Mental Wellness support
• Learning & Development programs
• And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work

Location: This role is based out of our Seattle, WA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesday through Friday, with flexibility to work remotely on Mondays. We believe connection fuels innovation, and our in-office culture is designed to support meaningful teamwork and mentorship.

ABOUT THIS OPPORTUNITY

onX is seeking a Staff Software Engineer who will contribute to meaningful, real-world outcomes that have a lasting impact for customers and the business. In this role, you’ll focus on the design, development, and scaling of our core AI/ML platforms and product-facing services as part of the AI Foundations Team, supporting the integration of cutting-edge artificial intelligence solutions across onX's product lines. You’ll take ownership of your work, collaborate closely with partners across the organization, and help move initiatives forward in an environment where priorities evolve, learning is celebrated, and you’re encouraged to keep stretching your skills. This role will report to the Director of Engineering.

WHAT YOU'LL DO
^{Essential Job Duties & Functions}

• Work on the design, development, and deployment of large-scale AI systems and services, including models, pipelines, product experiences and infrastructure.
• Help Drive the technical strategy and roadmap for AI feature development, focusing on scalability, repeatability, reliability, and performance.
• Mentor and guide other engineers in best practices and productionizing AI technologies.
• Collaborate with Product and Data Science teams to translate business problems into technical requirements and deliver high-impact AI solutions (combining LLMs, Vector Databases, ML and other technology in novel ways to serve onX’ unique audience).
• Look for opportunities to embed AI as a repeatable mechanism in daily workflows by integrating experimentation into real work, and continuously refining its use with sound judgment and validation.
• Be a leader in AI safety, ensuring AI-enabled products are aligned with our values and mission.
• Look for opportunities to embed AI as a repeatable co-pilot in daily workflows by integrating experimentation into real work, and continuously refining its use with sound judgment and validation.

WHAT YOU’LL BRING

• Bachelor’s degree in Computer Science, Data Science, or a related technical field, or equivalent experience.
• 10+ years of professional software engineering experience, with at least 3 years focused on building and scaling production AI/ML systems, is required.
• Expertise in building scalable backend systems.
• Deep knowledge of MLOps practices, cloud infrastructure (AWS/GCP/Azure), and CI/CD pipelines for machine learning models and the common inference APIs/SDKs and frameworks.
• Experience with modern AI technologies, including Large Language Models (LLMs) and their various architectures, methods such as RAG, vector databases, and the common AI stack including TensorFlow/Keras, PyTorch, Transformers, etc.
• A strong curiosity for exploring new technologies, including AI
• A shared passion for and ability to demonstrate onX’s Company Values.
• Permanent US work authorization is a condition of employment with onX.

ADDED BONUSES

Though not required, we would be thrilled to consider candidates with any of the following:

• A history of engaging in AI development, from the early ML/NN (YOLO, Darknet) to the LLM era.
• Experience in monitoring and debugging production AI systems (inference, evals, judging, benchmarks) including cost and performance optimizations.
• Interest or experience in edge/on-device inference (MLX, JAX, transformers on TPU/NPU, etc.)
• Interest, experience or experimentation in training/fine-tuning transformer/diffusion models, dataset curation and captioning, etc.

THE ONX EXPERIENCE

onX is a distributed company with more than 400 employees across the country. We come together regularly to work in person and stay connected through regional basecamps and a culture that balances individual ownership with deep collaboration.

While we move quickly, we’re not a scrappy start-up. We operate with clear goals, structure, and frameworks that guide how we prioritize and execute. Priorities matter. While they may shift, data shapes how we evolve as our business, products, and the world around us change.

Clear priorities and structure don’t limit ownership - they make it possible. You’ll have the autonomy to define your work and make meaningful decisions within clear strategic boundaries. You’ll partner closely with others to solve complex problems and build solutions that scale across teams and platforms. Along the way, you’ll be supported with feedback, tools, and opportunities to grow your craft as you take on new challenges.

WHERE YOU CAN WORK

onX has created a thriving distributed workforce designed to foster connection, collaboration, and shared experience across several US locations. We have two HQ locations in Bozeman and Missoula, MT and established virtual workforce Basecamps in Austin, TX; Denver, CO; Kalispell, MT; Minneapolis, MN; Portland, OR; Salt Lake City, UT; and Seattle, WA.

HOW YOU’LL BE COMPENSATED

onX is committed to compensating all employees fairly and equitably for their contributions.  Applicants can expect to make between $169,000 to $211,000 upon hire. The pay range will vary based on experience, skills, certifications, and education among other factors as required in the job description. In addition, full-time onX employees are eligible for a grant of common share options with a vesting schedule and a potential annual bonus of 10% based on company performance.

WHAT WE’RE OFFERING YOU

• Competitive salaries, annual bonuses, equity, and opportunities for growth
• Comprehensive health benefits, including a no-monthly-cost medical plan
• Paid parental leave of 13 weeks for birthing parents and 5 weeks for non-birthing parents
• 401k matching at 100% for the first 3% you save and 50% from 3-5%
• Company-wide outdoor adventures and amazing outdoor industry perks
• Annual “Get Out, Get Active” funds to fuel your active lifestyle
• Flexible time away package that includes PTO, STO, VTO, and paid holidays

PERFORMANCE ESSENTIALS

In this role, success is driven by cognitive abilities such as concentration and problem-solving, essential for our computer-centric tasks. onX will explore reasonable accommodations to ensure that individuals with diverse abilities can fully engage in and contribute to the essential physical and mental functions of the job. If you need assistance or accommodation, please contact us at PC@onxmaps.com. 

Application Deadline is [day of week], [month] [day] at [0:00 pm] MST

Position open until filled. 

#LI-Remote

We are seeking an innovative and experienced Embodied AI Researcher, focusing on the development and application of foundation models in robotics. The successful candidate will contribute to cutting-edge research, designing models and experiments that advance the field of robotics through deep learning and zero-shot generalization.

Responsibilities:

• Train foundation models for robotics, utilizing architectures similar to RT-X.
• Align text-based reasoning processes with low-level robotic control policies.
• Design and conduct experiments to evaluate zero-shot generalization in robotic systems.
• Collaborate with interdisciplinary teams to integrate AI models into practical robotic applications.
• Document and present research findings at internal and external conferences.

Qualifications:

• PhD or equivalent research experience in Deep Learning and Robotics.
• Proven track record of publications in top-tier conferences such as CoRL, ICRA, and NeurIPS.
• Practical experience with imitation learning and behavior cloning techniques.
• Strong programming skills in Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.
• Excellent problem-solving skills and the ability to work independently and as part of a team.

We are seeking a highly skilled LLM Pre-training & Distributed Systems Engineer. This role is essential for orchestrating large-scale machine learning training runs and optimizing  distributed infrastructure. The ideal candidate will have a deep understanding of GPU clusters and extensive experience in system engineering to ensure efficient and reliable training processes.

Responsibilities:

• Orchestrate distributed training runs across 1,000+ GPUs using PyTorch, DeepSpeed, or Megatron-LM.
• Optimize networking (InfiniBand/RDMA) and memory management to prevent out-of-memory errors.
• Automate checkpointing and failure recovery during month-long training runs.

Required Skills:

• Deep expertise in 3D parallelism (Data, Tensor, Pipeline).
• Experience managing SLURM or Kubernetes-based GPU clusters.
• Strong systems engineering background (C++, CUDA, Python).

Senior ML Engineer - Healthcare AI Innovation

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values.

This position is based out of our headquarters in the Greater Seattle area.  #LI-hybrid

What You'll Do

• Build & Innovate: Design and implement advanced ML models and systems using large-scale EHR data
• Explore New Frontiers: Identify and develop novel use cases for AI in healthcare that have not yet been widely explored
• Work Across Modalities: Leverage structured and unstructured clinical data, and integrate emerging data types such as genomics, imaging, and clinical notes
• Translate Research into Practice: Prototype new ideas and evolve them into production-ready solutions
• Collaborate Broadly: Partner with clinicians, researchers, product teams, and external stakeholders (e.g., pharma, life sciences organizations)
• Deliver Impact: Build solutions that enable better decision-making for customers and ultimately improve patient outcomes 

What We're Looking For

Basic Qualifications

• • Bachelor’s or Master’s degree (or PhD) in Computer Science, Machine Learning, or a related field
  • Strong foundation in machine learning, deep learning, or applied statistics
  • Experience building and deploying ML models in real-world settings
  • Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow) 

Preferred Qualifications

• • Experience working with healthcare or biomedical data (EHRs, clinical notes, genomics, imaging)
  • Familiarity with modern ML approaches such as:
  • Large language models / foundation models
  • Multimodal learning 
  • Causal inference
  • Time-series and longitudinal modeling
  • Experience bridging research and engineering (e.g., taking ideas from papers to production)
  • Publications or demonstrated innovation in applied ML (a plus, not required) 

Why Truveta?

Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional, and everything in between. Join us as we build an amazing company together.

We Offer:

• Interesting and meaningful work for every career stage
• Great benefits package
• Comprehensive benefits with strong medical, dental and vision insurance plans
• 401K plan
• Professional development & training opportunities for continuous learning
• Work/life autonomy via flexible work hours and flexible paid time off
• Generous parental leave
• Regular team activities (virtual and in-person)
• The base pay for this position is $175,000 to $200,000. The pay range reflects the minimum and maximum target. Pay is based on several factors including location and may vary depending on job-related knowledge, skills, and experience. Certain roles are eligible for additional compensation such as incentive pay and stock options.

If you are based in California, we encourage you to read this important information for California residents linked here.

Truveta is committed to creating a diverse, inclusive, and empowering workplace. We believe that having employees, interns, and contractors with diverse backgrounds enables Truveta to better meet our mission and serve patients and health communities around the world. We recognize that opportunities in technology historically excluded and continue to disproportionately exclude Black and Indigenous people, people of color, people from working class backgrounds, people with disabilities, and LGBTQIA+ people. We strongly encourage individuals with these identities to apply even if you don’t meet all of the requirements.

Please note that all applicants must be authorized to work in the United States for any employer as we are unable to sponsor work visas or permits (e.g. F-1 OPT, H1-B) at this time. We appreciate your interest in the position and encourage you to explore future opportunities with us.

Machine Learning Engineer - LLMs & Generative AI

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values.

This position is based out of our headquarters in the Greater Seattle area.  #LI-hybrid

Who We Need 

Truveta is building a diverse and inclusive team to tackle complex health and technical challenges. We are seeking enthusiastic new graduates who are problem-solvers, collaborative teammates, and eager to make a difference in healthcare. If you’re excited about purposeful work, joining a mission-driven team, and launching your career in a supportive environment, Truveta could be the perfect place to start.

This Opportunity 

We are looking for a Machine Learning Engineer with a deep background in generative AI, large language models (LLMs), and reinforcement learning techniques to build the next generation of AI systems for trustworthy healthcare. This role offers a unique opportunity to build foundational models trained on vast clinical data and drive innovation in a highly meaningful domain.

Responsibilities

• Lead the development, training, and deployment of large language and multimodal foundation models tailored to clinical and biomedical domains.
• apply and refine state-of-the-art techniques such as supervised fine-tuning (SFT), reinforcement learning-based methods (e.g., RLHF, RLVR), parameter-efficient fine-tuning (PEFT), prompt tuning, and retrieval-augmented generation (RAG).
• Collaborate cross-functionally with researchers, clinicians, and engineers to design ML-driven solutions that improve healthcare delivery and outcomes.
• Build scalable infrastructure for distributed training of large models (TPU/GPU clusters, multi-node orchestration).
• Design and evaluate models for robustness, bias mitigation, factual consistency, and explainability in healthcare contexts.
• Stay current with the latest research in generative AI and contribute back to the community through publications and open-source initiatives.

Minimum Qualifications

• 6+ years of experience in software engineering or machine learning (3+ years with a PhD).
• Experience designing and training LLMs or large-scale generative models (e.g., GPT, PaLM, LLaMA, Claude, Gemma).
• Deep expertise in NLP, sequence modeling, and transformer architectures.
• Proficient in Python and ML libraries such as PyTorch or TensorFlow; strong engineering skills in building scalable ML pipelines.
• Experience with RL-based fine-tuning (e.g., Reinforcement Learning from Human Feedback) and evaluation of generative systems.
• Proven ability to lead technical projects and collaborate across teams.
• Bachelor's degree in Computer Science, Engineering, or a related technical field

Preferred Qualifications

• PhD or equivalent experience in Machine Learning, NLP, AI, or a related field.
• Experience in healthcare, biomedical informatics, or clinical data modeling.
• Familiarity with multi-modal foundation models (e.g., text-image, text-structured data) and cross-modal alignment techniques.
• Hands-on experience with vector databases, semantic search, and retrieval-based generation
• Publications in top-tier ML conferences (NeurIPS, ICML, ACL, EMNLP, ICLR, etc.).
• Experience building trustworthy AI systems and applying model interpretability, fairness, and safety frameworks.

Why Truveta?

Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional, and everything in between. Join us as we build an amazing company together.

We Offer:

• Interesting and meaningful work for every career stage
• Great benefits package
• Comprehensive benefits with strong medical, dental and vision insurance plans
• 401K plan
• Professional development & training opportunities for continuous learning
• Work/life autonomy via flexible work hours and flexible paid time off
• Generous parental leave
• Regular team activities (virtual and in-person)
• The base pay for this position is $155,000 to $175,000. The pay range reflects the minimum and maximum target. Pay is based on several factors including location and may vary depending on job-related knowledge, skills, and experience. Certain roles are eligible for additional compensation such as incentive pay and stock options.

If you are based in California, we encourage you to read this important information for California residents linked here.

Truveta is committed to creating a diverse, inclusive, and empowering workplace. We believe that having employees, interns, and contractors with diverse backgrounds enables Truveta to better meet our mission and serve patients and health communities around the world. We recognize that opportunities in technology historically excluded and continue to disproportionately exclude Black and Indigenous people, people of color, people from working class backgrounds, people with disabilities, and LGBTQIA+ people. We strongly encourage individuals with these identities to apply even if you don’t meet all of the requirements.

Please note that all applicants must be authorized to work in the United States for any employer as we are unable to sponsor work visas or permits (e.g. F-1 OPT, H1-B) at this time. We appreciate your interest in the position and encourage you to explore future opportunities with us.

ML PhD Intern - LLMs & Generative AI

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values.

Our headquarters are in the greater Seattle area, but we celebrate and embrace a remote culture.  Participation in the internship program requires that you are physically present in the United States for the duration of the internship. #LI-remote

Who We Need 

We are seeking a highly motivated and talented Machine Learning PhD Intern to join our AI research team and contribute to our innovative projects in the field of Large Language Modeling (LLM) and clinical data analysis. Beyond core capabilities, we are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference. If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, Truveta may be the perfect fit for you.

Internship Details

Our Research PhD Internship is designed for candidates who have finished their classes and are working only on research work to complete their PhD. Candidates must be within 1 year of their graduation date from their PhD program. Candidates are expected to demonstrate both independence in defining their research strategy within a domain as well as an ability to apply innovative solutions to our products. Our internships are designed to be a minimum of 10 weeks with the opportunity to extend beyond the initially agreed term based on the company’s needs and the candidate’s desires.

This Opportunity

We are looking for machine learning experts who can utilize applied science and software development skills in building our Foundation Models that help us address some of the hardest problems towards our vision of Saving Lives with Data. You will work in an exciting and fast-paced environment, collaborating closely with multiple teams across the company. You will work as part of an organization that brings together talent from diverse backgrounds including software engineering, big data, machine learning and AI, clinical informatics, and medicine making our team an exciting place to work. We value and encourage diversity in the belief that our differences make us and our products better.

In this role, you will:

• Collaborate with researchers and engineers to design, develop, and refine large language models and generative models for various applications.
• Utilize your expertise in machine learning and natural language processing to develop novel algorithms and methodologies for generative modeling tasks.
• Implement, train, and fine-tune LLM and GPT-like models on large-scale datasets to ensure optimal performance and accuracy.
• Stay up to date with the latest research advancements and techniques in the field of language modeling, generative modeling, and machine learning.
• Deliver the next generation of innovation in trustworthy healthcare.

Key Qualifications

• Currently pursuing a Ph.D. in Computer Science, Electrical Engineering, or a related field, with a focus on machine learning, natural language processing (NLP), Large Language Models (LLMs), multi-modal foundation models, and generative AI
• Strong theoretical and practical background in NLP including experience with state-of-the-art architectures
• Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow, etc.) and libraries commonly used in NLP and Generative AI
• Solid programming skills in Python and the ability to write clean, efficient, and well-documented code
• Excellent problem-solving and troubleshooting abilities, along with a strong analytical mindset and persistence in resolving problems
• Strong communication skills and the ability to work effectively in a collaborative research environment

Preferred Qualifications

• Experience with distributed parallel training, large-scale multi-modal foundation and generative models
• Familiarity with parameter-efficient tuning techniques, Reinforcement Learning from Human Feedback (RLHF), and prompt engineering techniques
• Familiarity with training multi-modal foundation models
• Familiarity with cloud-based infrastructure and experience deploying large-scale machine learning models in production environments
• A track record of publications and contributions to the machine learning and natural language processing communities

This internship opportunity offers a unique chance to work on state-of-the-art language models and contribute to transformative research with the vision of Saving Lives with Data. You will be part of a dynamic team of researchers and engineers who are passionate about pushing the boundaries of machine learning and natural language understanding in the healthcare domain. Join us and make a significant impact on the future of healthcare and patient well-being.

Why Truveta? 

Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional and everything in between. Join us as we build an amazing company together. 

We offer: 

• Competitive compensation
• Company-issued laptop and equipment
• Opportunities for future full-time positions
• The hourly pay for this position is $45

Truveta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

ML Postdoc Researcher - LLMs & Generative AI

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values.

Our headquarters are in the greater Seattle area, but we celebrate and embrace a remote culture.  Participation in the Postdoctoral Research program requires that you are physically present in the United States for the duration of the program. #LI-remote

Who We Need 

We are seeking a highly motivated and talented Machine Learning Postdoctoral Researcher to join our AI research team and contribute to our innovative projects in the field of Large Language Modeling (LLM) and clinical data analysis. Beyond core capabilities, we are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference. If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, Truveta may be the perfect fit for you.

Program Details

Our Postdoctoral Research program is designed for candidates who have completed their PhD within the last two years and worked in their area of expertise since graduation as a postdoc, professor, or industry researcher/scientist. Candidates are expected to demonstrate both independence in defining their research strategy within a domain as well as an ability to apply innovative solutions to our products. Our postdoc research programs are designed to be a minimum of 3 months and a maximum of 12 months, with the opportunity to extend beyond the initially agreed term based on the company’s needs and the candidate’s desires.

This Opportunity

We are looking for machine learning experts who can utilize applied science and software development skills in building our Foundation Models that help us address some of the hardest problems towards our vision of Saving Lives with Data. You will work in an exciting and fast-paced environment, collaborating closely with multiple teams across the company. You will work as part of an organization that brings together talent from diverse backgrounds including software engineering, big data, machine learning and AI, clinical informatics, and medicine making our team an exciting place to work. We value and encourage diversity in the belief that our differences make us and our products better.

In this role, you will:

• Collaborate with researchers and engineers to design, develop, and refine large language models and generative models for various applications.
• Utilize your expertise in machine learning and natural language processing to develop novel algorithms and methodologies for generative modeling tasks.
• Implement, train, and fine-tune LLM and GPT-like models on large-scale datasets to ensure optimal performance and accuracy.
• Stay up to date with the latest research advancements and techniques in the field of language modeling, generative modeling, and machine learning.
• Deliver the next generation of innovation in trustworthy healthcare.

Key Qualifications

• Ph.D. in Computer Science, Electrical Engineering, or a related field, with a focus on machine learning, natural language processing (NLP), Large Language Models (LLMs), multi-modal foundation models, and generative AI
• Strong theoretical and practical background in NLP including experience with state-of-the-art architectures
• Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow, etc.) and libraries commonly used in NLP and Generative AI
• Solid programming skills in Python and the ability to write clean, efficient, and well-documented code
• Excellent problem-solving and troubleshooting abilities, along with a strong analytical mindset and persistence in resolving problems
• Strong communication skills and the ability to work effectively in a collaborative research environment

Preferred Qualifications

• Experience with distributed parallel training, large-scale multi-modal foundation and generative models
• Familiarity with parameter-efficient tuning techniques, Reinforcement Learning from Human Feedback (RLHF), and prompt engineering techniques
• Familiarity with training multi-modal foundation models
• Familiarity with cloud-based infrastructure and experience deploying large-scale machine learning models in production environments
• A track record of publications and contributions to the machine learning and natural language processing communities

This postdoctoral research program offers a unique chance to work on state-of-the-art language models and contribute to transformative research with the vision of Saving Lives with Data. You will be part of a dynamic team of researchers and engineers who are passionate about pushing the boundaries of machine learning and natural language understanding in the healthcare domain. Join us and make a significant impact on the future of healthcare and patient well-being.

Why Truveta? 

Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional and everything in between. Join us as we build an amazing company together. 

We offer: 

• Competitive compensation
• Company-issued laptop and equipment
• Opportunities for future full-time positions
• The range for this position is $50-$60 per hour

Truveta is committed to creating a diverse, inclusive, and empowering workplace. We believe that having employees, interns, and contractors with diverse backgrounds enables Truveta to better meet our mission and serve patients and health communities around the world. We recognize that opportunities in technology historically excluded and continue to disproportionately exclude Black and Indigenous people, people of color, people from working class backgrounds, people with disabilities, and LGBTQIA+ people. We strongly encourage individuals with these identities to apply even if you don’t meet all of the requirements.

Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter.

Our base salary range is $170,000 - $220,000, and in addition we have generous bonus plans to provide a competitive compensation package. 

Who We Are: 

We are a non-profit AI institute, focused on developing foundational AI research and innovation to deliver real-world impact through large-scale open models, data, and artifacts (e.g., Olmo, Tulu, Molmo).   We unite the best and brightest scientific and engineering minds to explore the potential of truly open AI. Through  our efforts, including the pioneering Olmo releases, we endeavor to empower academics, researchers, and AI developers more broadly to advance language models and generative AI models. Through close collaboration, we rapidly identify, define, and act on the most exciting and promising new ideas in AI.  

Our team engages in a broad range of AI research, including pre-training and post-training language models, curating data to enhance AI across different modalities, and developing novel methodologies to push the field forward. We study and evaluate AI models both theoretically and empirically, aiming to advance their capabilities. Additionally, we create impactful real-world applications, such as in scientific synthesis. Our goal is to develop state-of-the-art models that excel in scientific discovery, reasoning, and factual recall.

Who You Are: 

You are a talented, hands-on engineer who thrives in a fast-paced environment, is self-directed, a team player, and knows how to get things done. You have a deep knowledge of Python, infrastructure, and a strong understanding of modern deep learning, natural language processing, language models, and the inner workings of the transformer architecture. You can translate high-level goals into concrete research and implementation steps, set an approach, follow through, and present results. When it’s time to explain your ideas, you bring clarity to complex technical issues. You use these skills to create real-world benefits for researchers and other practitioners, and you are excited to help advance our effort to create the best-performing open AI model.

Your Next Challenge:

You will be a part of the core team of research and machine learning engineers working on the infrastructure, architecture, modeling and training of Olmo (Open Language Model) at all stages: pre-training, mid-training, post-training and all emerging paradigms. In this role you will be owning the design and implementation of the systems that train these models. You will be responsible for building scalable machine learning pipelines as we push the boundaries of large language modeling research. You will be collaborating with colleagues inside and outside your own team, but you are responsible for a feature or experiment from start to finish, from conception to implementation.

The essential functions include, but are not limited to the following:

• Building infrastructure to facilitate the next generation of LLM research
• Optimizing training and inference for language models
• Triaging between experiments and executing on the most impactful
• Supporting and collaborating with an open-source community
• Bridging the gap between cutting-edge research and a widely adopted product
• Bringing software engineering best practices to a research environment
• Releasing your contributions back to the broader community in the form of open source software, model releases, and additions to Ai2’s public API and open research datasets, as well as technical reports

What You’ll Need: 

• Expertise at building ML infrastructure - having 4+ years of industry experience building infrastructure that handles data preprocessing/transformation and model training, evaluation, inference, and deployment
• Deep experience in the complete model development cycle, including data set construction, training, tuning, evaluation, performance profiling, and monitoring
• Knowledge of modern deep learning and natural language processing techniques
• Strong software engineering skills, particularly around building performant systems and debugging
• At-home with hands-on programming – must have experience with Python and PyTorch/Jax/Tensorflow. We expect you to be the kind of engineer who can pick up a new programming language, library, or API as needed without it being a big deal.
• Familiarity working with cloud compute resources (e.g. AWS) and containerization (e.g. Docker)
• Strong collaboration and communication skills - our environment is small and collaborative, and we'd like you to thrive while working closely with others, sometimes with complementary skills/perspectives

Bonus qualifications:

• Advanced degree in Data Science/CS/EE/Applied Mathematics/Statistics/ML/NLP or related fields and/or relevant and equivalent engineering experience
• Contributions to open-source ML or research libraries (e.g. spaCy, AllenNLP, transformers)
• Experience successfully operating models at scale in a production setting
• Experience in HPC settings
• Curiosity about AI research

Education:

• BS or MSc in Computer Science, Statistics, Engineering, Applied Mathematics, or a related quantitative field

Physical Demands and Work Environment:

The physical demands described here are representative of those that must be met by a team member to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the functions.

• Must be able to remain in a stationary position for long periods of time.
• The ability to communicate information and ideas so others will understand. Must be able to exchange accurate information in these situations.
• The ability to observe details at close range.
• Can work under deadlines.

A Little More About Ai2:

The Allen Institute for Artificial Intelligence is a non-profit research institute in Seattle founded by Paul Allen. The core mission of Ai2 is to contribute to humanity through high-impact research in artificial intelligence. 

In addition to Ai2’s core mission, we also aim to contribute to humanity through our treatment of each member of the Ai2 Team. Some highlights are:

• We are a learning organization – because everything Ai2 does is ground-breaking, we are learning every day. Similarly, through weekly Ai2 Academy lectures, a wide variety of world-class AI experts as guest speakers, and our commitment to your personal on-going education, Ai2 is a place where you will have opportunities to continue learning alongside your coworkers. 
• We value diversity - We seek to hire, support, and promote people from all genders, ethnicities, and all levels of experience regardless of age. We particularly encourage applications from women, non-binary individuals, people of color, members of the LGBTQA+ community, and people with disabilities of any kind. 
• We value inclusion - We understand the value that people's individual experiences and perspectives can bring to an organization, and we are building a culture in which all voices are heard, respected and considered.
• We emphasize a healthy work/life balance – we believe our team members are happiest and most productive when their work/life balance is optimized. While we value powerful research results which drive our mission forward, we also value dinner with family, weekend time, and vacation time. We offer generous paid vacation and sick leave as well as family leave.
• We are collaborative and transparent – we consider ourselves a team, all moving with a common purpose. We are quick to cheer our successes, and even quicker to share and jointly problem solve our failures.
• We are in Seattle – and our office is on the water! We have mountains, we have lakes, we have four seasons, we bike to work, we have a vibrant theater scene, and we have so much else. We even have kayaks for you to paddle right outside our front door. We welcome interest from applicants from outside of the United States.
• We are friendly– chances are you will like every one of the 200+ people who work here. We do. 

Ai2 is proud to be an Equal Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. You may view the related Know Your Rights compliance poster and the Pay Transparency Nondiscrimination Provision by clicking on their corresponding links. 

This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. If E-Verify cannot confirm that you are authorized to work, this employer is required to give you written instructions and an opportunity to contact the Department of Homeland Security (DHS) or Social Security Administration (SSA) so you can begin to resolve the issue before the employer can take any action against you, including terminating your employment. Employers can only use E-Verify once you have accepted a job offer and completed the Form I-9.

We are committed to providing reasonable accommodations to employees and applicants with disabilities to the full extent required by the Americans with Disabilities Act (ADA). If you feel you need a reasonable accommodation pursuant to the ADA, you are encouraged to contact us at recruiting@allenai.org.

Benefits:

• Team members and their families are covered by medical, dental, vision, basic life insurance, basic accidental death and dismemberment insurance, short-term disability, long-term disability, and an employee assistance program.
• Team members are able to enroll in our voluntary life insurance program, our voluntary accidental death and dismemberment program, our health savings account plan, our healthcare reimbursement arrangement plan, and our health care and dependent care flexible spending account plans.
• Team members are able to enroll in our company’s 401k plan.
• Team members will receive $125 per month to assist with commuting or internet expenses and will also receive $200 per month for fitness and wellbeing expenses.
• Team members will also receive up to ten sick days per year, up to seven personal days per year, up to 20 vacation days per year and twelve paid holidays throughout the calendar year.
• Team members will be able to receive annual bonuses and can participate in the long-term incentive plan.

Note: This job description in no way states or implies that these are the only duties to be performed by the team members(s) of this position. Team members will be required to follow any other job-related instructions and to perform any other job-related duties requested by any person authorized to give instructions or assignments. All duties and responsibilities are essential functions and requirements and are subject to possible modification to reasonably accommodate individuals with disabilities. To perform this job successfully, the team member(s) will possess the skills, aptitudes, and abilities to perform each duty proficiently. Some requirements may exclude individuals who pose a direct threat or significant risk to the health or safety of themselves or others. The requirements listed in this document are the minimum levels of knowledge, skills, or abilities. This document does not create an employment contract, implied or otherwise, other than an at will relationship.

Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter.

Our base salary range is $128,880 - $193,320, and in addition we have generous bonus plans to provide a competitive compensation package.

Who You Are:

Ai2 is seeking talented and motivated Research Engineer, working on the next generation of  large language model architectures , with a focus on Mixture-of-Experts (MoE), long-context language models (LCLMs), and flexible data use.. 

You are a talented, hands-on engineer who thrives in a fast-paced environment, is self-directed, a team player, and knows how to get things done. You have a strong understanding of modern deep learning, natural language processing, language models, and the inner workings of the transformer architecture, especially MoEs. You can translate high-level goals into concrete research and implementation steps, set an approach, follow through, and present results. When it’s time to explain your ideas, you bring clarity to complex technical issues. You use these skills to create real-world benefits for researchers and other practitioners, and you are excited to help advance our effort to create the best-performing open AI model.

Who We Are: 

We are a non-profit AI institute, focused on developing foundational AI research and innovation to deliver real-world impact through large-scale open models, data, and artifacts (e.g., OLMo, Tulu, Asta, OlmoEarth).   We unite the best and brightest scientific and engineering minds to explore the potential of truly open AI. Through  our efforts, we endeavor to empower academics, researchers, and AI developers more broadly to advance language models and generative AI models. Through close collaboration, we rapidly identify, define, and act on the most exciting and promising new ideas in AI.  

The FlexOlmo team designs new architectures and training methods that help models use data more effectively—through improved training, inference-time conditioning, and retrieval—broadening the types of data they can leverage and ultimately enhancing performance. We also develop scientific methodologies for evaluating and understanding these systems. Our team produces high-impact research and expertly engineered open-source tools that accelerate NLP research worldwide. Our first release in July 2025 focused on a new Mixture-of-Experts architecture. Looking ahead, we plan to pursue creative, groundbreaking research that delivers scientific insights and practical solutions for building architectures and training methods that unlock the use of large and diverse data sources.

Your Next Challenge:

You will be a part of the core team of research engineers working on the infrastructure, architecture, modeling and training of the next generation of architectures of foundation models, with a focus on continual learning. In this role you will be owning the design and implementation of the systems that train these models. You will be responsible for building scalable machine learning pipelines as we push the boundaries of large language modeling research. You will be collaborating with colleagues inside and outside your own team, but you are responsible for a feature or experiment from start to finish, from conception to implementation.

The essential functions include, but are not limited to the following:

• Building infrastructure to facilitate the next generation of LLM research. 
• Optimizing training and inference for language models.
• Triaging between experiments and executing on the most impactful.
• Bridging the gap between cutting-edge research and a widely adopted product.
• Bringing software engineering best practices to a research environment.
• Supporting and collaborating with an open-source community.
• Releasing your contributions back to the broader community in the form of open source software, model releases, and additions to Ai2’s public API and open research datasets, as well as technical reports.

What You’ll Need:

• A bachelor’s degree in Data Science/CS/EE/Applied Mathematics/Statistics/ML/NLP, or a related field, or equivalent relevant experience, and expertise at building ML infrastructure.
• 4+ years of experience building infrastructure that handles data preprocessing/transformation and model training, evaluation, inference, and deployment. Experience in the complete model development cycle, including data set construction, training, tuning, evaluation, performance profiling, and monitoring.
• Knowledge of modern deep learning and natural language processing techniques.
• Strong software engineering skills, particularly around building performant systems and debugging.
• Must have experience with Python and PyTorch/Jax/Tensorflow as well as feel at ease in picking up new programming languages, libraries, or APIs  as tools as project needs evolve.
• Familiarity working with cloud compute resources (e.g. AWS) and containerization (e.g. Docker).
• Strong collaboration and communication skills - our environment is small and collaborative, and we'd like you to thrive while working closely with others, sometimes with complementary skills/perspectives.

Bonus qualifications:

• Advanced degree in Data Science/CS/EE/Applied Mathematics/Statistics/ML/NLP or related fields and/or relevant and equivalent engineering experience.
• Contributions to open-source ML or research libraries (e.g. spaCy, AllenNLP, transformers).
• Experience successfully operating models at scale in a production setting.
• Experience in HPC settings.
• Curiosity about AI research.

Physical Demands and Work Environment:

The physical demands described here are representative of those that must be met by a team member to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the functions.

• Must be able to remain in a stationary position for long periods of time. 
• The ability to communicate information and ideas so others will understand. Must be able to exchange accurate information in these situations. 
• The ability to observe details at close range.
• Can work under deadlines.

A Little More About Ai2:

Ai2 is a Seattle based non-profit AI research institute founded in 2014 by the late Paul Allen. Our mission is building breakthrough AI to solve the world’s biggest problems. We develop foundational AI research and innovation to deliver real-world impact through large-scale open models, data, robotics, conservation, and beyond.

In addition to Ai2’s core mission, we also aim to contribute to humanity through our treatment of each member of the Ai2 Team. Some highlights are:

• We are a learning organization – because everything Ai2 does is ground-breaking, we are learning every day. Similarly, through weekly Ai2 Academy lectures, a wide variety of world-class AI experts as guest speakers, and our commitment to your personal on-going education, Ai2 is a place where you will have opportunities to continue learning alongside your coworkers. 
• We value diversity - We seek to hire, support, and promote people from all genders, ethnicities, and all levels of experience regardless of age. We particularly encourage applications from women, non-binary individuals, people of color, members of the LGBTQA+ community, and people with disabilities of any kind. 
• We value inclusion - We understand the value that people's individual experiences and perspectives can bring to an organization, and we are building a culture in which all voices are heard, respected and considered.
• We emphasize a healthy work/life balance – we believe our team members are happiest and most productive when their work/life balance is optimized. While we value powerful research results which drive our mission forward, we also value dinner with family, weekend time, and vacation time. We offer generous paid vacation and sick leave as well as family leave.
• We are collaborative and transparent – we consider ourselves a team, all moving with a common purpose. We are quick to cheer our successes, and even quicker to share and jointly problem solve our failures.
• We are in Seattle – and our office is on the water! We have mountains, we have lakes, we have four seasons, we bike to work, we have a vibrant theater scene, and we have so much else. We even have kayaks for you to paddle right outside our front door. We welcome interest from applicants from outside of the United States.
• We are friendly– chances are you will like every one of the 200+ (and growing) people who work here. We do. 

Ai2 is proud to be an Equal Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. You may view the related Know Your Rights compliance poster and the Pay Transparency Nondiscrimination Provision by clicking on their corresponding links. 

This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. If E-Verify cannot confirm that you are authorized to work, this employer is required to give you written instructions and an opportunity to contact the Department of Homeland Security (DHS) or Social Security Administration (SSA) so you can begin to resolve the issue before the employer can take any action against you, including terminating your employment. Employers can only use E-Verify once you have accepted a job offer and completed the Form I-9.

We are committed to providing reasonable accommodations to employees and applicants with disabilities to the full extent required by the Americans with Disabilities Act (ADA). If you feel you need a reasonable accommodation pursuant to the ADA, you are encouraged to contact us at recruiting@allenai.org.

Benefits:

• Team members and their families are covered by medical, dental, vision, basic life insurance, basic accidental death and dismemberment insurance, short-term disability, long-term disability, and an employee assistance program.
• Team members are able to enroll in our voluntary life insurance program, our voluntary accidental death and dismemberment program, our health savings account plan, our healthcare reimbursement arrangement plan, and our health care and dependent care flexible spending account plans.
• Team members are able to enroll in our company’s 401k plan.
• Team members will receive $125 per month to assist with commuting or internet expenses and will also receive $200 per month for fitness and wellbeing expenses.
• Team members will also receive up to ten sick days per year, up to seven personal days per year, up to 20 vacation days per year and twelve paid holidays throughout the calendar year.
• Team members will be able to receive annual bonuses and can participate in the long-term incentive plan.

Note: This job description in no way states or implies that these are the only duties to be performed by the team members(s) of this position. Team members will be required to follow any other job-related instructions and to perform any other job-related duties requested by any person authorized to give instructions or assignments. All duties and responsibilities are essential functions and requirements and are subject to possible modification to reasonably accommodate individuals with disabilities. To perform this job successfully, the team member(s) will possess the skills, aptitudes, and abilities to perform each duty proficiently. Some requirements may exclude individuals who pose a direct threat or significant risk to the health or safety of themselves or others. The requirements listed in this document are the minimum levels of knowledge, skills, or abilities. This document does not create an employment contract, implied or otherwise, other than an at will relationship.

ABOUT THIS OPPORTUNITY

We are looking for a Data Scientist who views machine learning as a product, not just a research project. You will be a foundational member of our AI team, responsible for designing, building, and deploying sophisticated models that solve complex business problems. You aren't just an expert in XGBoost or Transformers; you are an expert in building the pipelines that make these models reliable, scalable, and impactful.

WHAT YOU'LL DO
^{Essential Job Duties & Functions}

• End-to-End Model Development: Design and implement the full ML lifecycle—from exploratory data analysis (EDA) and feature engineering to model selection, tuning, and validation.
• GCP Architecture: Leverage the full Google Cloud AI suite (Vertex AI, BigQuery ML, Dataflow, and Pub/Sub) to build robust, cloud-native ML solutions.
• MLOps & Engineering: Implement CI/CD for machine learning (CT - Continuous Training) to ensure models remain performant in production environments.
• Strategic Leadership: Partner with stakeholders to translate ambiguous business challenges into technical roadmaps. Mentor junior scientists and advocate for best practices in code quality and experiment tracking.
• Look for opportunities to embed AI as a repeatable co-pilot in daily workflows by integrating experimentation into real work, and continuously refining its use with sound judgment and validation.

WHAT YOU’LL BRING

• 5+ years in a professional Data Science role with a track record of deploying models at scale.
• Proficiency in Vertex AI, BigQuery, Cloud Storage, and Looker. Experience with Kubeflow is a major plus.
• Expert-level Python (pandas, scikit-learn, PyTorch/TensorFlow), Spark, and advanced SQL.
• Deep understanding of statistics and ML theory (e.g., Gradient Descent, Bias-Variance tradeoff, Bayesian inference).
• Experience with ETL/ELT processes, specifically using dbt.
• A strong curiosity for exploring new technologies, including AI
• A shared passion for and ability to demonstrate onX’s Company Values.
• Permanent US work authorization is a condition of employment with onX.

Our Tech Stack

• Data Warehouse: BigQuery
• Orchestration: Airflow (Cloud Composer)
• Modeling: Vertex AI Pipelines, JupyterLab
• Deployment: Docker, GKE (Google Kubernetes Engine)

Pro Tip for the Candidate: We value "clean code" as much as "smart math." If you treat your notebooks like production scripts and your Git history is a work of art, you’ll fit right in.

What Sets You Apart

• The "Product" Mindset: You understand that a model with 99% accuracy is useless if it costs more to run than the value it creates.
• Infrastructure as Code: You are comfortable with Terraform or similar tools to manage your cloud resources.
• Communication: You can explain the "why" behind a complex neural network architecture to an executive without using jargon.

THE ONX EXPERIENCE

onX is a distributed company with more than 400 employees across the country. We come together regularly to work in person and stay connected through regional basecamps and a culture that balances individual ownership with deep collaboration.

While we move quickly, we’re not a scrappy start-up. We operate with clear goals, structure, and frameworks that guide how we prioritize and execute. Priorities matter. While they may shift, data shapes how we evolve as our business, products, and the world around us change.

Clear priorities and structure don’t limit ownership - they make it possible. You’ll have the autonomy to define your work and make meaningful decisions within clear strategic boundaries. You’ll partner closely with others to solve complex problems and build solutions that scale across teams and platforms. Along the way, you’ll be supported with feedback, tools, and opportunities to grow your craft as you take on new challenges.

WHERE YOU CAN WORK

onX has created a thriving distributed workforce designed to foster connection, collaboration, and shared experience across several US locations. We have two HQ locations in Bozeman and Missoula, MT and established virtual workforce Basecamps in Austin, TX; Denver, CO; Kalispell, MT; Minneapolis, MN; Portland, OR; Salt Lake City, UT; and Seattle, WA.

HOW YOU’LL BE COMPENSATED

onX is committed to compensating all employees fairly and equitably for their contributions. For this position, applicants can expect to make between $126,000 to $149,000 upon hire. The pay range will vary based on experience, skills, certifications, and education among other factors as required in the job description. In addition, full-time onX employees are eligible for a grant of common share options with a vesting schedule and a potential annual bonus of 10% based on company performance.

WHAT WE’RE OFFERING YOU

• Competitive salaries, annual bonuses, equity, and opportunities for growth
• Comprehensive health benefits, including a no-monthly-cost medical plan
• Paid parental leave of 13 weeks for birthing parents and 5 weeks for non-birthing parents
• 401k matching at 100% for the first 3% you save and 50% from 3-5%
• Company-wide outdoor adventures and amazing outdoor industry perks
• Annual “Get Out, Get Active” funds to fuel your active lifestyle
• Flexible time away package that includes PTO, STO, VTO, and paid holidays

PERFORMANCE ESSENTIALS

In this role, success is driven by cognitive abilities such as concentration and problem-solving, essential for our computer-centric tasks. onX will explore reasonable accommodations to ensure that individuals with diverse abilities can fully engage in and contribute to the essential physical and mental functions of the job. If you need assistance or accommodation, please contact us at PC@onxmaps.com. 

Application Deadline is [day of week], [month] [day] at [0:00 pm] MST

Position open until filled. 

#LI-Remote

Your Impact

We are seeking a skilled and innovative Senior AI Research Scientist to join a new team focusing on agentic video and multimodal reasoning systems. As a research scientist at Axon you will play a crucial role in developing AI solutions that transform both the enterprise and public safety domains and support our company’s mission: accelerate justice, protect truth, and save lives. You will advance the state-of-the-art in machine learning and multimodal technology and apply your research findings to create new responsible AI capabilities for Axon products. You will collaborate with product managers, engineers and cross-functional teams to train models and develop cutting-edge algorithms and solutions that enable intelligent perception and understanding of visual and multimodal data.

At Axon, we Aim Far. We think big with a long-term view because we want to reinvent the world to be a safer, better place. If you’re excited about this role and our mission to Protect Life but your experience doesn’t align perfectly with every qualification listed here, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

What You’ll Do

Reports to: Director of AI Research
Location: This role is based out of our Seattle, WA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesdays through Fridays, with the flexibility to work remotely on Mondays, unless there is an approved workplace accommodation. We believe that connection fuels innovation, and our in-office culture is designed to foster meaningful teamwork, mentorship, and shared success.

• Collaborate with other scientists, engineers and product managers to build proof-of-concepts to shape the Axon of tomorrow.
• Lead end-to-end research efforts in AI-assisted universal search of and reasoning over large multimodal data with an emphasis on video understanding.
• Advance related computer vision, machine learning and gen-AI techniques for cloud and devices from multimodal data sources, including scene understanding, action recognition and anomaly detection.
• Design and implement responsible, privacy-preserving, efficient and scalable models for inference and analysis of visual data.
• Develop performance and quality metrics for agentic multimodal reasoning models and systems, and validate their effectiveness in real-world settings.
• Stay up-to-date with the latest research and advances in agentic AI, machine learning and computer vision and translate relevant findings into shipping Axon products.
• Contribute to academic publications, technical documentation, and patent disclosures to share insights and findings with the broader community.
• Coach and mentor junior scientists.

What You Bring

• PhD and 3+ years of experience in Computer Science or a related field with a focus on multimodal machine learning, large language models, video understanding, information retrieval, agentic reasoning or related technical fields.
• Proven track record of applied research and/or production impact in multimodal learning, video-language modeling, retrieval systems, foundation models, agentic systems, or RAG architectures.
• Experience owning and driving the ML development lifecycle from problem definition and data strategy through model development, evaluation, deployment, and iteration in production environments.
• Experience contributing to large-scale ML and multimodal RAG systems including embeddings, indexing and vector search at scale, distributed training or inference workflows, evaluation and ranking optimization, agentic tool use, and grounding LLMs with external knowledge.
• Strong understanding of video analysis and temporal modeling as well as computer vision fundamentals and trade-offs.
• Excellent problem-solving skills, analytical thinking, and the ability to work independently as well as collaboratively in a team environment.
• Proficiency in Python and frameworks such as PyTorch, TensorFlow or Keras.
• Strong communication skills and the ability to effectively present complex technical concepts to both technical and non-technical audiences.

Benefits that Benefit You

• Competitive salary and 401k with employer match
• Discretionary paid time off
• Paid parental leave for all
• Medical, Dental, Vision plans
• Fitness Programs
• Emotional & Mental Wellness support
• Learning & Development programs
• And yes, we have snacks in our offices

The Pay: Axon is a total compensation company, meaning compensation is made up of base pay, bonus, and stock awards. The starting base pay for this role is between USD 159,750 in the lowest geographic market and USD 234,300 in the highest geographic market. The actual base pay is dependent upon many factors, such as: level, function, training, transferable skills, work experience, business needs, geographic market, and often a combination of all these factors. Our benefits offer an array of options to help support you physically, financially and emotionally through the big milestones and in your everyday life. To see more details on our benefits offerings please visit www.axon.com/careers/benefits.

#LI-Hybrid

Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We are seeking a Research Engineer to join our Pre-training team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems.

Key Responsibilities:

• Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development
• Independently lead small research projects while collaborating with team members on larger initiatives
• Design, run, and analyze scientific experiments to advance our understanding of large language models
• Optimize and scale our training infrastructure to improve efficiency and reliability
• Develop and improve dev tooling to enhance team productivity
• Contribute to the entire stack, from low-level optimizations to high-level model design

Qualifications:

• Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field
• Strong software engineering skills with a proven track record of building complex systems
• Expertise in Python and experience with deep learning frameworks (PyTorch preferred)
• Familiarity with large-scale machine learning, particularly in the context of language models
• Ability to balance research goals with practical engineering constraints
• Strong problem-solving skills and a results-oriented mindset
• Excellent communication skills and ability to work in a collaborative environment
• Care about the societal impacts of your work

Preferred Experience:

• Work on high-performance, large-scale ML systems
• Familiarity with GPUs, Kubernetes, and OS internals
• Experience with language modeling using transformer architectures
• Knowledge of reinforcement learning techniques
• Background in large-scale ETL processes

You'll thrive in this role if you:

• Have significant software engineering experience
• Are results-oriented with a bias towards flexibility and impact
• Willingly take on tasks outside your job description to support the team
• Enjoy pair programming and collaborative work
• Are eager to learn more about machine learning research
• Are enthusiastic to work at an organization that functions as a single, cohesive team pursuing large-scale AI research projects
• Are working to align state of the art models with human values and preferences, understand and interpret deep neural networks, or develop new models to support these areas of research
• View research and engineering as two sides of the same coin, and seek to understand all aspects of our research program as well as possible, to maximize the impact of your insights
• Have ambitious goals for AI safety and general progress in the next few years, and you’re working to create the best outcomes over the long-term.

Sample Projects:

• Optimizing the throughput of novel attention mechanisms
• Comparing compute efficiency of different Transformer variants
• Preparing large-scale datasets for efficient model consumption
• Scaling distributed training jobs to thousands of GPUs
• Designing fault tolerance strategies for our training infrastructure
• Creating interactive visualizations of model internals, such as attention patterns

At Anthropic, we are committed to fostering a diverse and inclusive workplace. We strongly encourage applications from candidates of all backgrounds, including those from underrepresented groups in tech.

If you're excited about pushing the boundaries of AI while prioritizing safety and ethics, we want to hear from you!

About the Role:

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.

We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other’s words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us!

As an Engineering Manager, Machine Learning (ML) Operations in the Technology & Engineering division, you will be responsible for leading and managing PitchBook’s MLOps team. The team is responsible for enabling PitchBook’s Machine Learning teams and practitioners by providing tools and golden paths that optimize all aspects of the Machine Learning Development Life Cycle (MLDLC). Your team’s work will support projects in a variety of domains, including Generative AI (GenAI), Large Language Models (LLMs), Natural Language Processing (NLP), Classification, and Regression. Your role will be critical in driving AI (Artificial Intelligence) innovations across the organization.

Primary Job Responsibilities:

• Lead the MLOps team direction and execution (operations, processes, practices, and standards), working closely with engineering leadership and product management to craft roadmaps, define KPIs, and achieve success criteria
• Ensure effective communication and coordination across geographically dispersed teams. Oversee the enablement of scalable solutions that meet high standards of reliability and efficiency
• Champion the adoption and integration of ML best practices at PitchBook, fostering a culture of innovation and experimentation to drive the development of high-quality AI products
• Serve as a force multiplier by removing roadblocks, implementing process improvements, providing frequent and actionable feedback to team members, and building practices for ideation and innovation
• Bridge the gap between business/product needs and execution, including building and delivering on group-level objectives and key results, identifying resource needs, and building execution plans for initiatives
• Ensure MLOps roadmap items are delivered on time and have exceptional quality
• Learn constantly and be passionate about discovering new tools, technologies, libraries, and frameworks (commercial and open source), that can be leveraged to improve PitchBook’s AI capabilities
• Describe technical content in intuitive ways for a variety of audiences, adapting communication from highly technical deep dives with engineers to non-technical dialogue with executive stakeholders
• Establish and drive a culture founded on creating belonging, psychological safety, candor, connection, cooperation, and fun
• Understand how to apply agile, lean, and principles of fast flow to team efficiency and productivity 
• Support the vision and values of the company through role modeling and encouraging desired behaviors 
• Participate in various company initiatives and projects as requested 

Skills and Qualifications:

• Bachelor’s, Master’s, or PhD in Computer Science, Mathematics, Data Science, or a related field
• 3+ years of experience in an engineering leadership role, managing globally distributed teams
• 6+ years of experience in hands-on development of Machine Learning algorithms
• 6+ years of experience in hands-on deployment of Machine Learning services
• 6+ years of experience supporting the entire MLDLC, including post-deployment operations such as monitoring and maintenance
• 6+ years of experience with Amazon Web Services (AWS) and/or Google Cloud Platform (GCP)
• Experience with at least 70%: PyTorch, Tensorflow, LangChain, scikit-learn, Redis, Elasticsearch, Amazon SageMaker, Google Vertex AI, Weights & Biases, FastAPI, Prometheus, Grafana, Apache Kafka, Apache Airflow, MLflow, and KubeFlow
• Ability to break large, complex problems into well-defined steps, ensuring iterative development and continuous improvement
• Experience in cloud-native delivery with a deep practical understanding of containerization technologies such as Kubernetes and Docker, and the ability to manage these across different regions
• Proficiency in GitOps and creation/management of CI/CD pipelines
• Demonstrated experience building and using SQL/NoSQL databases
• Demonstrated experience with Python (Java is a plus) and other relevant programming languages and tools
• Excellent problem-solving skills with a focus on innovation, efficiency, and scalability in a global context
• Strong communication and collaboration skills, with the ability to engage effectively with internal customers across various cultures and regions
• Ability to be a team player who can also work independently
• Experience working across multiple development teams is a plus
• Proficiency with the Microsoft Office suite including in-depth knowledge of Outlook, Word, and Excel with the ability to pick up new systems and software easily 
• Must be authorized to work in the United States without the need for visa sponsorship now or in the future

Benefits + Compensation at PitchBook:

Physical Health            

• Comprehensive health benefits
• Additional medical wellness incentives 
• STD, LTD, AD&D, and life insurance

Emotional Health 

• Paid sabbatical program after four years
• Paid family and paternity leave 
• Annual educational stipend
• Ability to apply for tuition reimbursement
• CFA exam stipend 
• Robust training programs on industry and soft skills 
• Employee assistance program
• Generous allotment of vacation days, sick days, and volunteer days 

Social Health 

• Matching gifts program
• Employee resource groups
• Subsidized emergency childcare  
• Dependent Care FSA
• Company-wide events
• Employee referral bonus program  
• Quarterly team building events

Financial Health 

• 401k match
• Shared ownership employee stock program 
• Monthly transportation stipend  

*Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment.

Compensation

• Annual base salary: $240,000-$300,000
• Target annual bonus percentage: 15%

Working Conditions:

At the heart of our company is a belief in the power of in-person collaboration. Being together in the office fuels our creativity, strengthens our connections, and drives the innovation that sets us apart. Our culture is built on spontaneous moments—those hallway conversations, whiteboard brainstorms, and shared celebrations in each of our global offices—that simply can’t be replicated remotely. This role is expected to be in the office 5 days a week. 

The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.

We are excited to get to know you and your background. Concerned that you might not meet every requirement? We encourage you to still apply as you might be the right candidate for the role or other roles at PitchBook.

#LI-TK1

#LI-Onsite

At Amperity, we’re an AI-first company helping the world’s leading brands create personalized customer experiences that build loyalty and fuel growth. Our AI-powered Customer Data Cloud,  built on multi-patented technology, enables more than 400 global brands, including Alaska Airlines, Wyndham Hotels & Resorts, and DICK’S Sporting Goods, to turn customer data into a competitive advantage.

We unlock the full value of customer data with simplicity and speed. AI is at the core of our platform and the way we work — from powering advanced identity resolution and predictive analytics to streamlining internal workflows and decision-making. It’s not just a capability; it’s part of our DNA.

Our team thrives on curiosity, collaboration, and transparency, fostering a culture where everyone can contribute, learn, and grow. We welcome talented individuals from diverse backgrounds to help us remove data bottlenecks, accelerate business impact, and push the boundaries of what AI can do for the world’s most innovative companies.

With offices in Seattle, New York City, London, and Melbourne, you’ll join a fast-growing team tackling critical challenges at the intersection of AI, data, and customer experience. Ready to make an impact? Let’s talk.

The Role

At Amperity, ML Engineers work in small, collaborative, and accountable teams. As a Lead ML Engineer, you'll lead ML projects that span multiple teams, guiding both the technical direction and the platform capabilities that power our AI-driven products. You'll work with Applied Scientists, Software Engineers, Product, and Customer Success teams to deliver production ML systems that create measurable customer impact. We are an AI-first company. We expect engineers to embrace AI assistance tools like Claude Code as a core part of their daily workflow. They use these tools to accelerate development, improve code quality, and velocity. We keep our processes lightweight, our experimentation rigorous, and our focus on delivering value through machine learning.

Interesting Problems

We're solving tough problems at the intersection of large-scale data, AI, and user experience. Some of the challenges you might work on include:

• Architect ML platform components—feature stores, model registries, and serving infrastructure—that help teams across the organization to deploy models reliably and at scale.
• Build automated training and deployment pipelines that support model improvement for data drift and model degradation.
• Design real-time and batch feature engineering systems that power identity resolution, customer segmentation, and predictive models at enterprise scale.
• Improve model inference latency to deliver ML predictions that meet strict Service level agreements while managing infrastructure costs.
• Establish MLOps best practices, SLOs, and operational standards that ensure production ML systems are reliable, observable, and maintainable.

About You

You're a technical visionary who combines deep ML engineering expertise with systems building and experience building infrastructure that supports and scales several types of machine learning models. You take ownership of ML systems end-to-end—from model development through production operation—and help set the technical direction for ML engineering across the organization. You embrace AI-first practices, using tools like Claude Code to accelerate your work and advocating for their adoption across teams. You value influence, mentorship, and well-reasoned decisions.

• 8+ years of experience building production ML systems, with experience designing ML infrastructure and platforms.
• Technical leadership experience driving ML platform evolution or major ML projects across multiple teams.
• Expertise in ML deployment patterns, model serving, feature engineering, and monitoring/observability for ML systems.
• Software engineering skills with experience in Python and familiarity with ML frameworks (e.g. XGBoost, PyTorch, PySpark).
• Experience with cloud-native ML infrastructure, containerization, and orchestration (Kubernetes, Docker).
• Enthusiastic about AI-first development practices, with experience using AI coding assistants to accelerate engineering workflows.
• Turn ambiguous ML infrastructure problems into actionable plans, and guide teams through delivery.
• Experience aligning ML technical strategy with our priorities and customer needs.
• Mentor engineers, and improve how we build and operate ML systems.

Technologies To Know

We don't expect you to have experience with everything we use—but if you're excited about learning, you'll do great here. You'll influence and learn:

• Large-scale data engines like Apache Spark, Presto, and Kafka.
• MLOps tooling including MLflow, feature stores, and model serving frameworks.
• Cloud-native infrastructure built with Kubernetes and Terraform, deployed across multiple cloud providers.
• Functional programming languages including Clojure and Python for ML pipelines.
• Machine learning models for entity resolution, classification, and customer analytics.
• AI coding assistants (such as Claude Code) as part of our daily development workflow.

Location

Seattle, WA 

Our hybrid work model includes three days in the office each week, providing a mix of in-person collaboration and remote flexibility

Compensation

Base Salary:  $190,000-$260,000. Individual compensation within this range will depend on several factors, including your skills, experience, education/training, and the level at which you join. We also consider internal equity, market conditions, and overall business needs.

Cash Incentives: Cash incentives are also available.

Stock Options:  The opportunity for ownership is an exciting part of Amperity’s total compensation package. Every employee at Amperity receives a new-hire equity grant, commensurate with the scope of their position.

Benefits

We offer all the benefits you'd expect from a great place to work: 100% employee healthcare coverage, transportation subsidies, a comfortable work environment with plenty of snacks, and other employee experience perks like events and activities, both in-person and remote. We also offer self-managed PTO and the flexibility to do your best work in the way that works for you. We provide an inclusive environment where you'll be challenged to find and unlock your full potential, surrounded by a team of world-class people driving for excellence. For more details on our benefits, please see our US Benefits & Perks Guide.

Amperity is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, sex (including pregnancy, childbirth, and reproductive health choices), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as someone with a disability, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local law.

About the Role:

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.

We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other’s words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us! 

As a Senior Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role in delivering AI-powered features that extract meaningful insights from PitchBook’s wealth of structured and unstructured data including reports, news, and other textual content. This role requires deep technical expertise in advanced data analytics and machine learning, as well as a hands-on approach to designing, building, and optimizing ML solutions that power user-facing features on the PitchBook Platform.

You will be deeply involved in the end-to-end development and operationalization of ML models, including their architecture, training, deployment, and ongoing maintenance. Your focus will span across natural language processing (NLP), generative AI (GenAI), large language models (LLMs), and scalable data systems. You will be expected to tackle complex technical challenges, contribute to architectural decisions, and collaborate closely with other engineers, data scientists, and product managers to ensure that your work aligns with business goals and AI/ML strategy.

Your contributions will help unlock unique value for PitchBook customers by improving the speed, discoverability, quality, and quantity of insights available on the platform. This includes developing models that can infer meaning and structure from millions of discrete data sources, and applying ML to enrich our datasets with predictive and generative intelligence. As a senior engineer, you will take ownership of key technical components and ensure that our systems meet the highest standards of performance, reliability, and security.

Primary Job Responsibilities:

• Deliver high-impact AI and ML capabilities that drive insight generation on the PitchBook Platform. Ensure your work contributes to broader business goals and is aligned with the team's strategic priorities
• Provide hands-on expertise in designing, building, and deploying AI/ML models and services with a focus on NLP, summarization, semantic search, classification, and prediction. Contribute to the development of scalable, high-performance systems that meet production-grade reliability and efficiency standards
• Support a culture of technical excellence by mentoring peers, sharing knowledge, and participating in code and design reviews. Promote innovation and continuous improvement through collaborative engineering practices
• Build and optimize models that leverage classifiers, transformers, LLMs, and other NLP techniques to generate meaningful insights from structured and unstructured data. Integrate these models into the broader AI/ML infrastructure in collaboration with partner teams
• Collaborate with engineering, product management, and data collection teams to ensure models are informed by high-quality data and support strategic product goals
• Explore and experiment with emerging technologies, methodologies, and tools in the fields of GenAI, NLP, and search. Translate research findings into practical solutions that enhance PitchBook’s AI capabilities
• Contribute to best practices in model transparency, monitoring, evaluation, and compliance. Help maintain high standards of security, data integrity, and responsible AI use across your projects
• Participate in the technical evaluation of candidates and help onboard new team members by contributing to documentation, pairing, and knowledge-sharing practices
• Apply principles from Agile, Lean, and Fast-Flow methodologies to support efficient model development and deployment cycles
• Support the vision and values of the company through role modeling and encouraging desired behaviors 
• Participate in various company initiatives and projects as requested

Skills and Qualifications:

• Bachelor’s or advanced degree in Computer Science, Mathematics, Data Science, or a related technical field, advanced degree preferred
• 6+ years of experience in software engineering or machine learning engineering, with a strong focus on AI/ML applications in insight generation, summarization, semantic search, and prediction
• Demonstrated expertise in natural language processing (NLP) and machine learning, including hands-on experience with classifiers, transformer models, large language models (LLMs), and widely used ML and data science libraries such as scikit-learn, pandas, numpy, TensorFlow, and PyTorch
• Experience delivering production-grade GenAI or LLM-based systems with measurable business impact
• Familiarity with the LangChain ecosystem, including tools such as LangSmith and LangGraph, and experience using them in production environments is a strong plus
• Deep proficiency in building and maintaining scalable data pipelines and distributed systems using technologies such as Apache Kafka, Airflow, and cloud data platforms like Snowflake
• Strong programming skills in Python and SQL, with working knowledge of additional languages such as Java or Scala considered a plus
• Practical experience with cloud-native development, containerization, and orchestration technologies such as Docker and Kubernetes
• Demonstrated ability to solve complex technical problems, contribute to architectural decisions, and deliver high-performance, reliable solutions
• Excellent communication and collaboration skills, with experience working cross-functionally with product managers, engineers, and data scientists in globally distributed teams
• Experience working in fast-paced, data-driven environments. Prior exposure to fintech or financial data platforms is a strong advantage
• Experience authoring research papers for peer-reviewed AI/ML conferences (e.g., NeurIPS, ICML, ACL) and participating in the broader AI research community is strongly preferred
• Must be authorized to work in the United States without the need for visa sponsorship now or in the future

Benefits + Compensation at PitchBook:

Physical Health

• Comprehensive health benefits
• Additional medical wellness incentives
• STD, LTD, AD&D, and life insurance

Emotional Health

• Paid sabbatical program after four years
• Paid family and paternity leave
• Annual educational stipend
• Ability to apply for tuition reimbursement
• CFA exam stipend
• Robust training programs on industry and soft skills
• Employee assistance program
• Generous allotment of vacation days, sick days, and volunteer days

Social Health 

• Matching gifts program
• Employee resource groups
• Subsidized emergency childcare
• Dependent Care FSA
• Company-wide events
• Employee referral bonus program
• Quarterly team building events

Financial Health 

• 401k match
• Shared ownership employee stock program
• Monthly transportation stipend

*Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment.

Compensation

• Annual base salary: $170,000-$240,000
• Target annual bonus percentage: 10%

Working Conditions:

At the heart of our company is a belief in the power of in-person collaboration. Being together in the office fuels our creativity, strengthens our connections, and drives the innovation that sets us apart. Our culture is built on spontaneous moments—those hallway conversations, whiteboard brainstorms, and shared celebrations in each of our global offices—that simply can’t be replicated remotely. This role is expected to be in the office 5 days a week.

The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.

We are excited to get to know you and your background. Concerned that you might not meet every requirement? We encourage you to still apply as you might be the right candidate for the role or other roles at PitchBook.

#LI-MS1

#LI-Onsite

About the Role:

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.

We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other’s words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us! 

As a Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role in delivering AI-powered features that extract meaningful insights from PitchBook’s wealth of structured and unstructured data including reports, news, and other textual content. This role requires deep technical expertise in advanced data analytics and machine learning, as well as a hands-on approach to designing, building, and optimizing ML solutions that power user-facing features on the PitchBook Platform. 

You will be deeply involved in the end-to-end development and operationalization of ML models, including their architecture, training, deployment, and ongoing maintenance. Your focus will span across natural language processing (NLP), generative AI (GenAI), large language models (LLMs), and scalable data systems. You will be expected to tackle complex technical challenges, contribute to architectural decisions, and collaborate closely with other engineers, data scientists, and product managers to ensure that your work aligns with business goals and AI/ML strategy. 

Your contributions will help unlock unique value for PitchBook customers by improving the speed, discoverability, quality, and quantity of insights available on the platform. This includes developing models that can infer meaning and structure from millions of discrete data sources and applying ML to enrich our datasets with predictive and generative intelligence.  

Primary Job Responsibilities:

• Deliver high-impact AI and ML capabilities that drive insight generation on the PitchBook Platform. Ensure your work contributes to broader business goals and is aligned with the team's strategic priorities 
• Provide hands-on expertise in designing, building, and deploying AI/ML models and services with a focus on NLP, summarization, semantic search, classification, and prediction. Contribute to the development of scalable, high-performance systems that meet production-grade reliability and efficiency standards 
• Contribute to a culture of technical excellence by sharing knowledge, pairing with teammates, and actively participating in code and design reviews. Provide situational guidance to junior engineers and contribute to team best practices 
• Build and optimize models that leverage classifiers, transformers, LLMs, and other NLP techniques to generate meaningful insights from structured and unstructured data. Integrate these models into the broader AI/ML infrastructure in collaboration with partner teams
• Collaborate with engineering, product management, and data collection teams to ensure models are informed by high-quality data and support strategic product goals
• Explore and experiment with emerging technologies, methodologies, and tools in the fields of GenAI, NLP, and search. Translate research findings into practical solutions that enhance PitchBook’s AI capabilities 
• Contribute to best practices in model transparency, monitoring, evaluation, and compliance. Help maintain high standards of security, data integrity, and responsible AI use across your projects 
• Participate in the technical evaluation of candidates and help onboard new team members by contributing to documentation, pairing, and knowledge-sharing practices 
• Apply principles from Agile, Lean, and Fast-Flow methodologies to support efficient model development and deployment cycles 
• Support the vision and values of the company through role modeling and encouraging desired behaviors
• Participate in various company initiatives and projects as requested   

Skills and Qualifications:

• Bachelor’s degree in Computer Science, Mathematics, Data Science, or related technical field, advanced degrees are preferred 
• 2+ years of experience in software engineering or machine learning engineering, with a strong focus on AI/ML applications in insight generation, summarization, semantic search, and prediction 
• Demonstrated expertise in natural language processing (NLP) and machine learning, including hands-on experience with classifiers, transformer models, large language models (LLMs), and widely used ML and data science libraries such as scikit-learn, pandas, numpy, TensorFlow, and PyTorch
• Experience delivering production-grade GenAI or LLM-based systems with measurable business impact 
• Familiarity with the LangChain ecosystem, including tools such as LangSmith and LangGraph, and experience using them in production environments is a strong plus 
• Proficiency in building and maintaining scalable data pipelines and distributed systems using technologies such as Apache Kafka, Airflow, and cloud data platforms like Snowflake 
• Strong programming skills in Python and SQL, with working knowledge of additional languages such as Java or Scala considered a plus
• Practical experience with cloud-native development, containerization, and orchestration technologies such as Docker and Kubernetes
• Demonstrated ability to solve complex technical problems, contribute to architectural decisions, and deliver high-performance, reliable solutions
• Excellent communication and collaboration skills, with experience working cross-functionally with product managers, engineers, and data scientists in globally distributed teams
• Experience working in fast-paced, data-driven environments. Prior exposure to fintech or financial data platforms is a strong advantage
• Experience authoring research papers for peer-reviewed AI/ML conferences (e.g., NeurIPS, ICML, ACL) and participating in the broader AI research community is strongly preferred 
• Must be authorized to work in the United States without the need for visa sponsorship now or in the future

Benefits + Compensation at PitchBook:

Physical Health

• Comprehensive health benefits
• Additional medical wellness incentives
• STD, LTD, AD&D, and life insurance

Emotional Health

• Paid sabbatical program after four years
• Paid family and paternity leave
• Annual educational stipend
• Ability to apply for tuition reimbursement
• CFA exam stipend
• Robust training programs on industry and soft skills
• Employee assistance program
• Generous allotment of vacation days, sick days, and volunteer days

Social Health 

• Matching gifts program
• Employee resource groups
• Subsidized emergency childcare
• Dependent Care FSA
• Company-wide events
• Employee referral bonus program
• Quarterly team building events

Financial Health 

• 401k match
• Shared ownership employee stock program
• Monthly transportation stipend

*Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment.

Compensation

• Annual base salary: $125,000-$180,000
• Target annual bonus percentage: 10%

Working Conditions:

At the heart of our company is a belief in the power of in-person collaboration. Being together in the office fuels our creativity, strengthens our connections, and drives the innovation that sets us apart. Our culture is built on spontaneous moments—those hallway conversations, whiteboard brainstorms, and shared celebrations in each of our global offices—that simply can’t be replicated remotely. This role is expected to be in the office 5 days a week.

The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.

We are excited to get to know you and your background. Concerned that you might not meet every requirement? We encourage you to still apply as you might be the right candidate for the role or other roles at PitchBook.

#LI-MS1

#LI-Onsite

About the Role:

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.

We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other’s words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us!

As an Engineering Manager, Machine Learning (ML) Operations in the Technology & Engineering division, you will be responsible for leading and managing PitchBook’s MLOps team. The team is responsible for enabling PitchBook’s Machine Learning teams and practitioners by providing tools and golden paths that optimize all aspects of the Machine Learning Development Life Cycle (MLDLC). Your team’s work will support projects in a variety of domains, including Generative AI (GenAI), Large Language Models (LLMs), Natural Language Processing (NLP), Classification, and Regression. Your role will be critical in driving AI (Artificial Intelligence) innovations across the organization.

Primary Job Responsibilities:

• Lead the MLOps team direction and execution (operations, processes, practices, and standards), working closely with engineering leadership and product management to craft roadmaps, define KPIs, and achieve success criteria
• Ensure effective communication and coordination across geographically dispersed teams. Oversee the enablement of scalable solutions that meet high standards of reliability and efficiency
• Champion the adoption and integration of ML best practices at PitchBook, fostering a culture of innovation and experimentation to drive the development of high-quality AI products
• Serve as a force multiplier by removing roadblocks, implementing process improvements, providing frequent and actionable feedback to team members, and building practices for ideation and innovation
• Bridge the gap between business/product needs and execution, including building and delivering on group-level objectives and key results, identifying resource needs, and building execution plans for initiatives
• Ensure MLOps roadmap items are delivered on time and have exceptional quality
• Learn constantly and be passionate about discovering new tools, technologies, libraries, and frameworks (commercial and open source), that can be leveraged to improve PitchBook’s AI capabilities
• Describe technical content in intuitive ways for a variety of audiences, adapting communication from highly technical deep dives with engineers to non-technical dialogue with executive stakeholders
• Establish and drive a culture founded on creating belonging, psychological safety, candor, connection, cooperation, and fun
• Understand how to apply agile, lean, and principles of fast flow to team efficiency and productivity 
• Support the vision and values of the company through role modeling and encouraging desired behaviors 
• Participate in various company initiatives and projects as requested 

Skills and Qualifications:

• Bachelor’s, Master’s, or PhD in Computer Science, Mathematics, Data Science, or a related field
• 3+ years of experience in an engineering leadership role, managing globally distributed teams
• 6+ years of experience in hands-on development of Machine Learning algorithms
• 6+ years of experience in hands-on deployment of Machine Learning services
• 6+ years of experience supporting the entire MLDLC, including post-deployment operations such as monitoring and maintenance
• 6+ years of experience with Amazon Web Services (AWS) and/or Google Cloud Platform (GCP)
• Experience with at least 70%: PyTorch, Tensorflow, LangChain, scikit-learn, Redis, Elasticsearch, Amazon SageMaker, Google Vertex AI, Weights & Biases, FastAPI, Prometheus, Grafana, Apache Kafka, Apache Airflow, MLflow, and KubeFlow
• Ability to break large, complex problems into well-defined steps, ensuring iterative development and continuous improvement
• Experience in cloud-native delivery with a deep practical understanding of containerization technologies such as Kubernetes and Docker, and the ability to manage these across different regions
• Proficiency in GitOps and creation/management of CI/CD pipelines
• Demonstrated experience building and using SQL/NoSQL databases
• Demonstrated experience with Python (Java is a plus) and other relevant programming languages and tools
• Excellent problem-solving skills with a focus on innovation, efficiency, and scalability in a global context
• Strong communication and collaboration skills, with the ability to engage effectively with internal customers across various cultures and regions
• Ability to be a team player who can also work independently
• Experience working across multiple development teams is a plus
• Proficiency with the Microsoft Office suite including in-depth knowledge of Outlook, Word, and Excel with the ability to pick up new systems and software easily 
• Must be authorized to work in the United States without the need for visa sponsorship now or in the future

Benefits + Compensation at PitchBook:

Physical Health            

• Comprehensive health benefits
• Additional medical wellness incentives 
• STD, LTD, AD&D, and life insurance

Emotional Health 

• Paid sabbatical program after four years
• Paid family and paternity leave 
• Annual educational stipend
• Ability to apply for tuition reimbursement
• CFA exam stipend 
• Robust training programs on industry and soft skills 
• Employee assistance program
• Generous allotment of vacation days, sick days, and volunteer days 

Social Health 

• Matching gifts program
• Employee resource groups
• Subsidized emergency childcare  
• Dependent Care FSA
• Company-wide events
• Employee referral bonus program  
• Quarterly team building events

Financial Health 

• 401k match
• Shared ownership employee stock program 
• Monthly transportation stipend  

*Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment.

Compensation

• Annual base salary: $240,000-$300,000
• Target annual bonus percentage: 15%

Working Conditions:

At the heart of our company is a belief in the power of in-person collaboration. Being together in the office fuels our creativity, strengthens our connections, and drives the innovation that sets us apart. Our culture is built on spontaneous moments—those hallway conversations, whiteboard brainstorms, and shared celebrations in each of our global offices—that simply can’t be replicated remotely. This role is expected to be in the office 5 days a week. 

The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.

We are excited to get to know you and your background. Concerned that you might not meet every requirement? We encourage you to still apply as you might be the right candidate for the role or other roles at PitchBook.

#LI-TK1

#LI-Onsite

Your Impact

We are seeking a skilled and innovative Senior Research Scientist to join one of our AI teams focusing on computer vision and machine learning (CVML). As a research scientist at Axon you will play a crucial role in developing AI solutions that transform both the enterprise and public safety domains and support our company’s mission: accelerate justice, protect truth, and save lives. You will advance the state-of-the-art in CVML and multimodal technology and apply your research findings to create new responsible AI capabilities for Axon products. You will collaborate with product managers, engineers and cross-functional teams to train models and develop cutting-edge algorithms and solutions that enable intelligent perception and understanding of visual data.