We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.

Role Overview

What You Will do

• Design features and build large-scale machine learning models and systems to improve ad targeting, relevance, ranking, and engagement
• Design and implement large-scale ML systems for search ranking, semantic retrieval, query understanding, and personalized product discovery using state-of-the-art techniques such as transformer-based models, contrastive learning, and vector search
• Drive innovation in search relevance and user intent modeling using large language models (LLMs), embedding-based retrieval, and multi-modal learning
• Build and optimize ML pipelines using tools such as Apache Spark, Airflow, Kubeflow, and MLflow, ensuring reproducibility, scalability, and operational excellence
• Define and track key performance metrics to evaluate model impact and identify high[1]leverage opportunities for improvement
• Collaborate cross-functionally with product, engineering, and data science teams to align technical solutions with business goals and customer experience
• Mentor and grow engineering talent, fostering a culture of technical excellence, experimentation and continuous learning

Basic Qualifications

• Bachelor's degree in computer science, electrical engineering, mathematics, statistics or closely related fields
• 4 years of professional experience in applied machine learning
• Experience in machine learning, deep learning, and statistical modeling
• Proficiency in Python and/or Java, with experience in building production grade ML systems

Preferred Qualifications

• Master’s or PhD in relevant technical fields
• Experience with search systems, information retrieval or recommendation engines
• Experience with LLMs, embeddings, and vector search technologies
• Experience with cloud platforms such as AWS, Google Cloud Platform including services like Vertex AI, BigQuery or SageMaker
• Experience working in startup or high-growth environments
• Proven ability to lead-cross-functional teams and deliver results in a multicultural, global organization
• Hands-on experience with modern ML frameworks such as TensorFlow, PyTorch, Scikit[1]learn, Keras, XGBoost, LightGMB, and H2o.ai
• Experience with ML lifecycle tools such as MLflow, Kubeflow, Weights & Biases, or Amazon SageMaker
• Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders
• Demonstrated ability to work independently and manage ambiguity in fast-paced environments

Pay & Benefits

Our compensation reflects the cost of living across several US geographic markets. At Coupang, your base pay is one part of your total compensation.

The base pay for Staff position ranges from $152K/year to $277K/year. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience.

General Description of All Benefits

• Annual bonus is 0-20% of the base salary
• Medical/Dental/Vision/Life, AD&D insurance
• Flexible Spending Accounts (FSA) & Health Savings Account (HSA)
• Long-term/Short-term Disability
• Employee Assistance Program (EAP) program
• 401K Plan with Company Match
• 18-21 days of the Paid Time Off (PTO) a year based on the tenure
• 12 Public Holidays
• 6 weeks Paid Parental leave
• Pre-tax commuter benefits
• MTV - [Free] Electric Car Charging Station

General Description of Other Compensation

“Other Compensation” includes, but is not limited to, bonuses, equity, or other forms of compensation that would be offered to the hired applicant in addition to their established salary range or wage scale.

Coupang is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to actual or perceived race (including traits historically associated with race, including but not limited to hair texture and protective hair styles), color, religion, religious creed (including religious dress and grooming practices), sex or gender (including pregnancy, childbirth, breastfeeding, and medical conditions related to pregnancy, childbirth or breastfeeding), gender identity, gender expression, sexual orientation, ,ancestry, national origin (including language use restrictions), age (40 and over), physical or mental disability, medical condition, genetic information, HIV/AIDS or Hepatitis C status, family status (including but not limited to marital or domestic partnership status), military or veteran status, use of a trained dog guide or service animal, political activities or affiliations, ancestry, citizenship, family and medical leave status, status as a victim of any violent crime, or any other characteristic or class protected by the laws or regulations in the locations where we operate.

Recruitment Process

• Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer

• The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances.

• Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage.

Details to Consider

• This job posting may be closed prior to the stated end date for application if all openings are filled.

• Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process.

• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.

Privacy Notice Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below: https://www.coupang.jobs/privacy-policy/

If you need assistance and/or a reasonable accommodation in the application of recruiting process due to a disability, please contact us at usrecruiting@coupang.com.

Job Req: R0069012

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

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.

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.

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 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 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 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

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 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.

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

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.

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.

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.

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.

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.

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 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.

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

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

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

Research Engineer, Multimodal Generative AI (Image/Video)

Seattle, WA

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

Snapshot

The role of the Research Engineer will be to develop state-of-the-art methods for multimodal generative AI models, with a primary focus on image generation and editing. This role is for the team behind “Nano Banana”.

At Google DeepMind, we've built a unique culture and work environment where long-term ambitious research can flourish. Our special interdisciplinary team combines the best techniques from deep learning, reinforcement learning, and systems neuroscience to build general-purpose learning algorithms. We have already made a number of high-profile breakthroughs towards building artificial general intelligence, and we have all the ingredients in place to make further significant progress over the coming year!

About Us

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

The Role

Research Engineers at Google DeepMind lead our efforts in developing novel tools, infrastructure, and algorithms towards the end goal of solving and building Artificial General Intelligence.

Having pioneered research in the world's leading academic and industrial labs, PhDs, post-docs, or professorships, Research Engineers join Google DeepMind to work collaboratively within and across Research fields. They are expected to independently build state of the art foundation models and research infrastructure, work with teams on large scale AI, and develop solutions to fundamental questions in machine learning and AI.

Drawing on expertise from a variety of disciplines including deep learning, computer vision, language modeling, and advanced generative architectures, our Research Engineers are at the forefront of groundbreaking research.

Key Responsibilities

• Design, rapidly implement, and rigorously evaluate cutting-edge deep learning algorithms, data curation, and evaluation infrastructure for multimodal generative AI, with a particular emphasis on image synthesis.
• Report and present research findings and developments clearly and efficiently both internally and externally, verbally and in writing.
• Suggest and engage in team collaborations to meet ambitious research goals, while also driving significant individual contributions.
• Work in collaboration with our Ethics and Governance teams to ensure our advances in intelligence are developed ethically and provide broad benefits to humanity.

About You

In order to set you up for success as a Research Engineer at Google DeepMind, we look for the following skills and experience:

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision, or equivalent practical experience.
• Proven experience in deep learning research and development, particularly in generative AI and related to image synthesis. This includes diffusion models and autoregressive generative models. Experience with post-training is a plus. 
• Exceptional engineering skills in Python and deep learning frameworks (e.g., Jax, TensorFlow, PyTorch), with a track record of building high-quality research prototypes and systems.
• Strong publication record at top-tier machine learning, computer vision, and graphics conferences (e.g., NeurIPS, ICLR, ICML, SIGGRAPH, CVPR, ICCV).

In addition, the following would be an advantage: 

Demonstrated experience in multimodal generative modeling, especially combining large language models with visual generation (e.g., text-to-image/video systems, joint autoregressive and diffusion models).A keen eye for visual aesthetics and detail, coupled with a passion for creating high-quality, visually compelling generative content.

• A real passion for AI!

What We Offer

At Google DeepMind, we want employees and their families to live happier and healthier lives, both in and out of work, and our benefits reflect that. Some select benefits we offer: enhanced maternity, paternity, adoption, and shared parental leave, private medical and dental insurance for yourself and any dependents, and flexible working options. We strive to continually improve our working environment, and provide you with excellent facilities such as healthy food, an on-site gym, faith rooms, terraces etc.

We are also open to relocating candidates to Mountain View and offer a bespoke service and immigration support to make it as easy as possible (depending on eligibility).

The US base salary range for this full-time position is between $166,000 USD - $244,000 USD + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

Note: In the event your application is successful and an offer of employment is made to you, any offer of employment will be conditional on the results of a background check, performed by a third party acting on our behalf. For more information on how we handle your data, please see our Applicant and Candidate Privacy Policy.