software engineer

machine learning engineer Jobs in San Francisco

machine learning engineer

ai engineer

ai engineer (gtm)

ai engineer – remote work Jobs in San Francisco

ai engineer – remote work

ml engineer

Ludo Robotics

<div>
 
 The Company
 
 
 
 LUDO ROBOTICS is dedicated to building general-purpose robotic intelligence systems that are robust, adaptive, and capable of handling real-world scenarios. We believe that data-driven machine learning at massive scale is the key to unlocking these capabilities and enabling the widespread deployment of robots across society.
 
 
 We are a new startup headquartered in Bay Area, California, with an office in Seoul, Korea. Our team spans a wide range of backgrounds and experience, from new graduates to seasoned domain experts. What matters most to us is ownership, speed, and intellectual curiosity - people who take responsibility, move fast, and enjoy thinking deeply about hard problems.
 
 
 We are supported by a highly advanced AI Center within KRAFTON, a leading global video game company best known for the genre-defining worldwide success PUBG: Battlegrounds. KRAFTON has extensive experience building and operating large-scale, data-rich products, and we have secured investment from them. This gives us strong long-term backing, deep technical partnership opportunities, and access to world-class infrastructure and talent networks as we push robotic intelligence forward.
 
 
 We are looking for passionate builders who want to explore uncharted territory, take on difficult problems, and ship ambitious, industry-shaping work. You will collaborate across diverse teams as we bring our technology from research into real-world deployment.
 
 
 
 THE OPPORTUNITY
 
 
 
 As an ML / AI Engineer at Ludo Robotics, you will develop scalable robotics systems that enable robots to operate reliably in the real-world environments. You will work with leading researchers and engineers on state-of-the-art methodologies to design and deploy algorithms and systems that enable robots to interact intelligently and adapt to diverse and complex environments. The ideal candidate has a strong technical background and experience in building practical solutions and driving real impact.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Lead and contribute to cutting-edge research and engineering problems at the frontier of robotic AI, including approaches and systems that have not been built before.
 </li>
 <li>
 Explore and develop new learning methods, architectures, and training strategies for robots facing unseen scenarios.
 </li>
 <li>
 Turn research ideas into deployed robot behavior, bridging theory and real-world performance.
 </li>
 <li>
 Collaborate with cross-functional teams spanning robotics software, hardware, data, and infrastructure.
 </li>
 <li>
 Influence technical direction and system design in a fast-moving startup environment.
 </li>
 <li>
 Access large-scale data, compute, and modern ML infrastructure to train and evaluate advanced models.
 </li>
 <li>
 Grow through ownership of open-ended problems where solutions are not predefined.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Degree in Computer Science, Electrical Engineering, or related field with focus on Deep Learning or Machine Learning
 </li>
 <li>
 Solid understanding of machine learning fundamentals and modern deep learning techniques, with hands-on experience with ML frameworks such as PyTorch or TensorFlow.
 </li>
 <li>
 Strong programming skills, primarily in Python, with experience or willingness to work in C++-based robotics environments.
 </li>
 <li>
 Comfort working on open-ended, ambiguous problems where requirements and solutions evolve and curiosity and readiness to tackle new technical challenges that may not have established best practices.
 </li>
 <li>
 Experience working with real-world data, including noise, edge cases, and imperfect labels.
 </li>
 <li>
 Familiarity with robotics concepts such as perception, control, state estimation, or simulation a plus.
 </li>
 <li>
 Strong problem-solving skills and the ability to reason about complex systems.
 </li>
 <li>
 Ability to collaborate effectively in fast-paced, research-driven environments.
 </li>
 <li>
 Clear communication skills and a strong sense of ownership over outcomes.
 
 
 </li>
 </ul>
 
 Reasonable Accommodation
 
 
 
 LUDO ROBOTICS is committed to the full inclusion of all qualified individuals. As part of this commitment, the Company will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to apply for an open position, perform essential job functions, and/or to receive other benefits and privileges of employment, please contact the Operations Team, to begin the interactive process.
 
 
 
 EEOC Statement
 
 
 
 LUDO ROBOTICS provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type.
 
 
 This position may be filled at multiple levels depending on experience, scope, and business need. In California, the expected salary range for this position is $98,000&ndash;$305,000. The listed expected salary ranges represent good faith estimates. Actual compensation may vary based on job-related factors including experience, education, skills, performance, and work location. This position is also eligible for equity compensation and a comprehensive benefits package.
 
 
 
 Don&rsquo;t meet every single requirement?
 
 
 
 Studies have shown that women and people of color are less likely to apply at jobs unless they meet every single qualification. At LUDO ROBOTICS we are dedicated to building a diverse, inclusive, and authentic workplace, so if you&rsquo;re excited about this role but your past experience doesn&rsquo;t align perfectly with every qualification in the job description, we encourage you to apply anyway. You might just be the right candidate for this or other roles.
 
 
 
 Due to recent scams, our recruiters will only reach out to you via @ludorobotics.ai, @sds.com, @krafton.com or @pubg.com. If you received an email and are unsure you can always email recruiting_KA@Krafton.com
 
</div>

ML/AI Engineer

Acceler8 Talent

<div>
 
 🚨
 
 Hiring: Machine Learning Engineer (Optimization / Decision Systems)
 
 
 
 📍 San Francisco (Onsite)
 
 
 💰 Up to $250K + Equity (Dependent on experience)
 
 
 
 
 
 Most companies still manage digital advertising like it&rsquo;s 2015. Manually adjusting budgets, guessing which campaigns work, and relying on black-box metrics from ad platforms.
 
 
 We&rsquo;re working with a venture-backed startup building something very different:
 
 
 An AI-driven optimization engine that autonomously allocates advertising spend using the same quantitative rigor used in high-frequency trading and financial markets.
 
 
 Instead of humans manually managing campaigns, their system continuously decides:
 
 
 &bull; Where budget should go
 
 
 &bull; When bids should change
 
 
 &bull; Which creative is losing performance
 
 
 &bull; How to maximize return across platforms
 
 
 
 
 
 
 What You&rsquo;ll Work On:
 
 
 
 🧠 Build models for LTV prediction and budget optimization
 
 
 ⚙️ Design risk-aware algorithms that control how millions in ad spend is deployed
 
 
 🔌 Build real-time integrations with platforms like Meta, Google &amp; TikTok
 
 
 📊 Develop simulation &amp; backtesting systems before strategies go live
 
 
 🚀 Take models from research &rarr; production &rarr; monitoring
 
 
 
 
 
 
 Ideal Background:
 
 
 
 ✔️ 4+ years in Machine Learning or Applied ML Engineering
 
 
 ✔️ Strong foundation in statistics, probability, and optimization
 
 
 ✔️ Experience deploying ML models in production systems
 
 
 ✔️ Builders who care about real-world impact, not just research
 
 
 
 
 
 ⭐ Bonus if you&rsquo;ve worked in quant finance, algorithmic trading, or adtech
 
 
 
 
 
 
 Why This Role Is Interesting:
 
 
 
 &bull; You&rsquo;ll build systems that control real-world financial decisions
 
 
 &bull; Early engineer helping shape the core architecture
 
 
 &bull; Opportunity to work on a $1T+ global market
 
 
 &bull; Meaningful equity at an early stage
 
 
 
 
 
 If you're interested or know someone who might be, DM me or apply below 👇👇
 
</div>

Machine Learning Engineer

ChatGPT Jobs

<div>
 
 Job Description
 
 
 
 Machine Learning Engineer
 
 
 
 Company:
 
 Harnham
 
 
 
 Location:
 
 San Francisco, CA
 
 
 <ul>
 <li>
 Remote
 
 
 </li>
 </ul>
 
 Type:
 
 Full-time
 
 
 
 Posted:
 
 10 hours ago
 
 
 
 Job Description
 
 
 
 
 MACHINE LEARNING ENGINEER - MULTIMODAL AI
 
 
 
 
 FULLY REMOTE
 
 
 
 
 $260,000 - $325,000
 
 
 
 An exciting opportunity for an experienced Machine Learning Engineer to join a team building next-generation multimodal AI systems for media generation. This role is ideal for someone with strong engineering skills, deep ML experience, and a passion for turning cutting-edge research into production-ready systems.
 
 
 You'll work on generative models for image and video, collaborating closely with engineering and product teams to bring AI-driven creative tools to life.
 
 
 
 The Company
 
 
 
 The company is a leader in AI-powered creative technology, pushing the boundaries of content creation on the browser. The engineering team is highly collaborative, fast-moving, and focused on building human-in-the-loop systems that scale.
 
 
 THE ROLE
 
 
 Hands-on engineering role focused on developing and deploying advanced ML models.
 
 
 <ul>
 <li>
 Develop computer vision and generative AI models for image and video
 </li>
 <li>
 Prototype and iterate on research solutions under tight timelines
 </li>
 <li>
 Collaborate with engineering, product, and research teams to productionize models
 </li>
 <li>
 Ensure clean, maintainable, and high-performance code
 
 
 </li>
 </ul>
 
 Your Skills &amp; Experience
 
 
 
 <ul>
 <li>
 5+ years in ML, computer vision, graphics, or related research/engineering roles
 </li>
 <li>
 Strong programming skills; experience with CUDA and C++ for performance optimizations
 </li>
 <li>
 Experience with at least one ML framework (PyTorch, TensorFlow)
 </li>
 <li>
 Deep interest in human-in-the-loop systems for creativity
 </li>
 <li>
 Ability to rapidly prototype and iterate on solutions
 </li>
 <li>
 Excellent collaboration, communication, and documentation skills
 
 
 </li>
 </ul>
 
 How To Apply
 
 
 
 Please register your interest by sending your resume to Calum Reid via the apply link on this page.
 
 
 
 About Harnham
 
 
 
 <ul>
 <li>
 Company size: 51 - 200 Employees
 </li>
 <li>
 Headquarters location: New York, NY, US
 </li>
 <li>
 Year founded: 2006
 </li>
 </ul>
</div>

Prolific

<div>
 <ul>
 <li>
 ]:pointer-events-auto scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" data-turn-id="7d8c6042-ac58-4acb-b90b-d08242002c4b" data-testid="conversation-turn-6" data-scroll-anchor="true" data-turn="assistant"&gt;
 </li>
 <li>
 ]:pointer-events-auto scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" data-turn-id="788a8b78-cfcd-42e1-beb1-30da5949a95d" data-testid="conversation-turn-8" data-scroll-anchor="true" data-turn="assistant"&gt;
 
 
 </li>
 </ul>
 
 AI Trainer &ndash; Machine Learning Specialists
 
 
 
 
 About Prolific
 
 
 
 Prolific is not just another player in the AI space &ndash; we are building the biggest pool of quality human data in the world.
 
 
 Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills.
 
 
 
 The role
 
 
 
 We're looking for
 
 AI Trainer &ndash; Machine Learning Specialists
 
 to help train and evaluate cutting-edge AI models using real ML expertise. If you have the necessary experience, we'll send you a quick
 
 10- to 15-minute test
 
 to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a participant, where you'll get paid to train and evaluate powerful AI models.
 
 
 Researchers looking for your skills tend to pay up to
 
 $150/hr per AI task completed
 
 . You must be prepared to complete paid tasks that require
 
 one hour of uninterrupted work
 
 , though many are shorter.
 
 
 What you'll bring
 
 
 <ul>
 <li>
 AI Training task skills and verifiable professional experience as a Machine Learning Specialist (e.g., ML engineer, data scientist, applied scientist, research engineer)
 </li>
 <li>
 A willingness to take our skills verification test to assess your suitability for our participant pool
 </li>
 <li>
 Strong attention to detail and the ability to concentrate on complex tasks for up to one hour at a time
 </li>
 <li>
 A reliable and fast internet connection and access to a computer
 </li>
 <li>
 A willingness to self-declare your earnings, as our participants are self-employed
 </li>
 <li>
 A Paypal account to receive payment from our clients
 
 
 </li>
 </ul>
 
 What you'll be doing in the role
 
 
 
 <ul>
 <li>
 Completing AI training tasks such as analyzing, editing, and writing annotations (including technical reasoning and structured evaluation)
 </li>
 <li>
 Judging the performance of AI in performing ML-relevant tasks (e.g., model/experiment critique, data leakage detection, metrics interpretation, debugging approach, methodology review)
 </li>
 <li>
 Improving cutting-edge AI models by providing expert feedback on correctness, robustness, clarity, and technical depth
 
 
 </li>
 </ul>
 
 Key Technologies
 
 
 
 <ul>
 <li>
 General AI Training
 </li>
 <li>
 Model Evaluation and Evals
 </li>
 <li>
 Trust and Safety
 </li>
 <li>
 Red Teaming
 </li>
 <li>
 Quality Analytics
 </li>
 <li>
 Data/ML Concepts (e.g., supervised learning, deep learning, NLP, CV, statistics, experimentation)
 
 
 </li>
 </ul>
 
 Why Prolific is a great platform to join as a Participant
 
 
 
 Joining our platform as a Prolific participant will give you the chance to influence the AI models of the future using professional machine learning expertise. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home.
 
 
 We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems.
 
 
 We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation &ndash; one that reflects the breath and the best of humanity.
 
 
 
 Links to more information on Prolific
 
 
 
 Website
 
 
 Youtube
 
 
 Privacy Statement
 
 
 By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.
</div>

AI Training - Machine Learning Specialist (PST)

Superhuman

<div>
 
 Superhuman offers a dynamic hybrid working model for this role. This flexible approach gives team members the best of both worlds: plenty of focus time along with in-person collaboration that helps foster trust, innovation, and a strong team culture.
 
 
 
 
 About Superhuman
 
 
 
 Grammarly is now part of Superhuman, the AI productivity platform on a mission to unlock the superhuman potential in everyone. The Superhuman suite of apps and agents brings AI wherever people work, integrating with over 1 million applications and websites. The company&rsquo;s products include Grammarly&rsquo;s writing assistance, Coda&rsquo;s collaborative workspaces, Mail&rsquo;s inbox management, and Go, the proactive AI assistant that understands context and delivers help automatically. Founded in 2009, Superhuman empowers over 40 million people, 50,000 organizations, and 3,000 educational institutions worldwide to eliminate busywork and focus on what matters.
 
 Learn more at superhuman.com and about our values here.
 
 
 
 
 The Opportunites
 
 
 
 We are building a platform for AI Agents to come together and solve arbitrarily complex tasks, leveraging Superhuman ubiquitous UI. As a Machine Learning Engineer on this team, you will be at the heart of our company's transformation.
 
 
 <ul>
 <li>
 Shape the Future of Productivity: Play a pivotal role in evolving Grammarly from a beloved writing assistant into an indispensable, AI-native productivity suite for enterprises.
 </li>
 <li>
 Build a Groundbreaking AI Agent Platform: Spearhead the development of a new platform where multiple AI agents collaborate to solve complex user problems. You will be responsible for the core orchestration, routing, and planning systems.
 </li>
 <li>
 Own Critical ML Systems: Develop and deploy sophisticated ML models for core product experiences, including search ranking and proactive suggestions that anticipate user needs.
 </li>
 <li>
 Integrate Cutting-Edge AI: Work at the forefront of the AI landscape, building ML components that integrate with the latest and most powerful models to create magical user experiences.
 </li>
 <li>
 Thrive in a High-Impact Environment: Join a foundational team where you will operate with a high degree of autonomy and product sense in a fast-paced, ambiguous environment.
 </li>
 <li>
 Ship Your Work Fast: Move quickly from idea to impact. We have no red tape or endless approvals&mdash;just a focus on making meaningful contributions to a platform used by millions.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 MS / PhD in Computer Science.
 </li>
 <li>
 5+ years of industry experience as a machine learning engineer or applied research scientist.
 </li>
 <li>
 A deep understanding of modern algorithms and approaches to ML, NLP, and LLMs.
 </li>
 <li>
 Experience building LLM-based products.
 </li>
 <li>
 A deep care about the end-user experience and strives to ensure high quality.
 </li>
 <li>
 Has a demonstrated ability to work independently with minimal guidance, proactively manages tasks and priorities across multiple projects, analyzes and executes work efficiently, collaborates effectively with cross-functional teams, and thrives in fast-paced, results-driven environments.
 
 
 </li>
 </ul>
 We invite you to share your knowledge, experience, and goals with us to help us find the best team match for you. Tell us your superpower!
 
 
 
 Compensation And Benefits
 
 
 
 Superhuman offers all team members competitive pay along with a benefits package encompassing the following and more:
 
 
 <ul>
 <li>
 Excellent health care (including a wide range of medical, dental, vision, mental health, and fertility benefits)
 </li>
 <li>
 Disability and life insurance options
 </li>
 <li>
 401(k) and RRSP matching
 </li>
 <li>
 Paid parental leave
 </li>
 <li>
 20 days of paid time off per year, 12 days of paid holidays per year, two floating holidays per year, and flexible sick time
 </li>
 <li>
 Generous stipends (including those for caregiving, pet care, wellness, your home office, and more)
 </li>
 <li>
 Annual professional development budget and opportunities
 
 
 </li>
 </ul>
 Superhuman takes a market-based approach to compensation, which means base pay may vary depending on your location. Our US locations are categorized into two compensation zones based on proximity to our hub locations.
 
 
 Base pay may vary considerably depending on job-related knowledge, skills, and experience. The expected salary ranges for this position are outlined below by compensation zone and may be modified in the future.
 
 
 United States
 
 
 Zone 1: $250,000 - $385,000/year (USD)
 
 
 
 We encourage you to apply
 
 
 
 At Superhuman, we value our differences, and we encourage all to apply&mdash;especially those whose identities are traditionally underrepresented in tech organizations. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, ancestry, national origin, citizenship, age, marital status, veteran status, disability status, political belief, or any other characteristic protected by law. Superhuman is an equal opportunity employer and a participant in the US federal E-Verify program (US). We also abide by the Employment Equity Act (Canada).
 
 
</div>

Machine Learning Engineer, Agents

Lila Sciences

<div>
 
 Your Impact at Lila
 
 
 
 We&rsquo;re seeking a Machine Learning Research Engineer for the Open-Endedness Team with expertise in large model training and optimizing novel algorithms for best results in distributed ML infrastructure. You&rsquo;ll design and maintain large-scale training systems, optimize performance for large models, and integrate cutting-edge techniques to improve efficiency and throughput.
 
 
 Open-Endedness is an emerging area of machine learning that aims to automate never-ending innovative processes of discovery and exploration. The Open-Endedness Team, led by Ken Stanley, investigates in particular how a continual chain of deep transformative creativity can be maintained that far exceeds the derivative creativity seen in current models. In effect, the systems developed on this team will go beyond simply solving problems posed by users, to conceiving the future unimagined directions of science itself.
 
 
 
 What You'll Be Building
 
 
 
 <ul>
 <li>
 Distributed training infrastructure for LLMs and multi-modal models.
 </li>
 <li>
 Performance optimizations for large-scale model training including training and optimization workflows (SFT, RL, long-context, etc.).
 </li>
 <li>
 Orchestrate frontier and open source LLMs along with complex compute-intensive tool use
 </li>
 <li>
 Scalable pipelines for data preprocessing and experiment orchestration, including tools for efficient data loading, pipeline parallelism, and optimizer tuning.
 </li>
 <li>
 System-level performance benchmarks and debugging utilities.
 
 
 </li>
 </ul>
 
 What You&rsquo;ll Need To Succeed
 
 
 
 <ul>
 <li>
 Proven experience with distributed ML training frameworks (Megatron-LM, TorchTitan, DeepSpeed, Ray).
 </li>
 <li>
 Strong software engineering skills (Python, C++ kernel contributions are a plus).
 </li>
 <li>
 Understanding of large-scale model training techniques.
 </li>
 <li>
 Experience with cloud or HPC environments.
 
 
 </li>
 </ul>
 
 Bonus Points For
 
 
 
 <ul>
 <li>
 Prior work with scientific datasets or domain-specific modeling.
 </li>
 <li>
 Contributions to open-source ML frameworks.
 
 
 </li>
 </ul>
 
 About Lila
 
 
 
 Lila Sciences is the world&rsquo;s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science.  We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method.  We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at  www.lila.ai
 
 
 If this sounds like an environment you&rsquo;d love to work in, even if you only have some of the experience listed below, we encourage you to apply.
 
 
 
 We&rsquo;re All In
 
 
 
 Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
 
 
 Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.
 
 
 
 A Note to Agencies
 
 
 
 
 Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science&rsquo;s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
 
 
 
 CompensationWe offer competitive compensation including bonus potential and generous early equity. The final offer will reflect your unique background, expertise, and impact.
 
 
 Expected Base Salary Range: $148,000 USD - $240,000 USD
</div>

Senior Machine Learning Research Engineer I/ II, Open-Endedness

Eli Lilly

<div>At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We&rsquo;re looking for people who are determined to make life better for people around the world.
Locations: San Diego, CA; San Francisco, CA; Boston, MA; Louisville, CO; Indianapolis, IN 
Lilly Small Molecule Discovery is purpose-built to create molecules that make life better for people. Discovery Technology and Platforms (DTP) accelerates molecule discovery by building optimized foundational platforms, streamlining lab operations through advanced technologies and data connectivity, and investing in novel capabilities.
Data Foundry is a multidisciplinary team within DTP that enables AI-native drug discovery through four integrated pillars: Architecture4Insight (data infrastructure and scientific software), Methods4Insight (analytical and computational methods), Automation &amp; Scale4Insight (lab automation and agentic workflows), and Preparedness4Insight (data governance and readiness). These pillars empower every Lilly scientist to make optimal decisions by providing seamless access to data, insights, and AI-driven capabilities&mdash;serving both human scientists and autonomous AI agents.
Position Summary
We are seeking an Engineer - MLOps &amp; Scientific Platforms - Data Foundry to operationalize Data Foundry&rsquo;s scientific tools and analytical methods into actionable-prototypes. You will build the ML deployment pipelines, model serving infrastructure, API layers, and observability guardrails that make our scientific discovery methods and tools reliable, scalable, and consumable, both by discovery scientists and by the Frontier AI group&rsquo;s autonomous agents.
This role sits at the interface between Methods4Insight (which develops analytical methods) and Architecture4Insight(which provides the agile data infrastructure). Your job is to ensure every scientific tool Data Foundry produces are analytics-ready, well-monitored, and exposed through APIs with the response-time guarantees and error handling that both human users and AI agents require.
Responsibilities<h2 class="jobSectionHeader">
MLOps &amp; Model Lifecycle Management</h2><ul><li>
Build and maintain end-to-end ML deployment pipelines: experiment tracking, model versioning (MLflow, Weights &amp; Biases), containerized model serving, and automated retraining triggers.</li><li>
Develop model registry infrastructure and feature engineering pipelines that enable computational scientists to access models.</li><li>
Implement monitoring and alerting for data pipelines, APIs, ML models, and agentic systems (LLMOps) to ensure system reliability and performance at scale.</li><li>
Build dashboards and metrics tracking for pipeline execution, API latency, token usage, model prediction quality, and system health</li><li>
Establish structured logging and tracing infrastructure for debugging and performance optimization across scientific data systems</li></ul><h2 class="jobSectionHeader">
Scientific Tool Agile Deployment</h2><ul><li>
Deploy predictive and analytical methods from Methods4Insight (e.g. cheminformatics, structural biology, bioinformatics, reaction informatics) with versioning, structured error handling, and response-time guarantees that enable insight generation in agile manner. Productionize when and where needed in partnerships with Tech@Lilly.</li><li>
Build serving infrastructure supporting both synchronous (interactive scientist queries) and asynchronous (batch and agent-invoked) workloads in partnership with Tech@Lilly and Frontier AI.</li><li>
Define and implement API contracts, documentation standards, and testing frameworks that ensure scientific tools are analysis ready, robust and consumable by external teams including Frontier AI.</li></ul><h2 class="jobSectionHeader">
Platform Engineering &amp; Integration</h2><ul><li>
Build and operate cloud-native model serving infrastructure (AWS, Azure, or GCP) using containers, Kubernetes, and infrastructure-as-code.</li><li>
Develop CI/CD pipelines for ML models: automated validation, A/B testing, canary deployments, and rollback procedures.</li><li>
Integrate model serving with Data Foundry&rsquo;s data pipelines, ensuring models have access to properly formatted, versioned training and inference data.</li></ul><h2 class="jobSectionHeader">
Frontier AI Interface &amp; Collaboration</h2><ul><li>
Partner with the Frontier AI team and Tech@Lilly to ensure Data Foundry&rsquo;s scientific tools are exposed via well-defined interfaces (REST APIs, MCP-compatible endpoints) that agents can invoke programmatically.</li><li>
Collaborate on API performance requirements: latency targets, throughput guarantees, and graceful degradation under load.</li><li>
Work with Methods4Insight scientists to ensure deployed models include appropriate uncertainty quantification and confidence metrics.</li></ul>
Basic Requirements<ul><li>
B.S. or M.S. in Computer Science, Data Science, Machine Learning, Bioinformatics, Computational Biology, or related field.</li><li>
3+ years of experience in MLOps, ML engineering, or scientific platform development</li><li>
Qualified applicants must be authorized to work in the United States on a full-time basis. Lilly will not provide support for or sponsor work authorization or visas for this role, including but not limited to F-1 CPT, F-1 OPT, F-1 STEM OPT, J-1, H-1B, TN, O-1, E-3, H-1B1, or L-1.</li></ul>
Preferred Qualifications<ul><li>
Pharmaceutical or biotech research industry experience.</li><li>
Strong Python skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and ML lifecycle tools (MLflow, W&amp;B, Kubeflow, or similar).</li><li>
Proven track record building and deploying production model serving infrastructure &mdash; containerized endpoints, RESTful/gRPC APIs, and operational monitoring</li><li>
Working knowledge of cloud platforms (AWS, Azure, or GCP), Kubernetes, and CI/CD automation.</li><li>
Strong communication skills with ability to collaborate across computational scientists, software engineers, and partner teams.</li><li>
Experience operationalizing scientific or computational models (cheminformatics, bioinformatics, structural biology, QSAR, molecular simulations, PK/PD, systems biology, or ODE-based models).</li><li>
Hands-on experience with model monitoring, drift detection, and automated retraining systems.</li><li>
Familiarity with API gateway patterns, event-driven architectures, and service mesh technologies.</li><li>
Experience with feature stores, data versioning (DVC), or experiment tracking at scale.</li><li>
Exposure to AI agent frameworks (MCP, LangChain) or building APIs that AI systems invoke programmatically.</li><li>
Experience with C, C++, CUDA, or GPU-accelerated computing for optimizing model training/inference performance; familiarity with containerizing HPC workloads (Singularity/Apptainer).</li></ul>
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status. 
Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia Network, Black Employees at Lilly, Chinese Culture Network, Japanese International Leadership Network (JILN), Lilly India Network, Organization of Latinx at Lilly (OLA), PRIDE (LGBTQ+ Allies), Veterans Leadership Network (VLN), Women&rsquo;s Initiative for Leading at Lilly (WILL), enAble (for people with disabilities). Learn more about all of our groups.
Actual compensation will depend on a candidate&rsquo;s education, experience, skills, and geographic location. The anticipated wage for this position is
$66,000 - $165,000
Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly&rsquo;s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.
#WeAreLilly</div>

Engineer - MLOps & Scientific Platforms - Data Foundry

Explore 113+ Ml engineer in San Francisco this March. Find roles across top companies and apply now to boost your career.

113 ml engineer jobs In San Francisco

ML/AI Engineer

Machine Learning Engineer

Machine Learning Engineer

AI Training - Machine Learning Specialist (PST)

Machine Learning Engineer, Agents

Senior Machine Learning Research Engineer I/ II, Open-Endedness

Engineer - MLOps & Scientific Platforms - Data Foundry