2026 Machine Learning Research Intern

Lambda, The Superintelligence Cloud, builds Gigawatt-scale AI Factories for Training and Inference. Lambda’s mission is to make compute as ubiquitous as electricity and give every person access to artificial intelligence. One person, one GPU.

If you'd like to build the world's best deep learning cloud, join us. 

*Note: This position requires presence in our San Francisco office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.

Join Lambda as a Machine Learning Research Intern and help advance the frontiers of generative AI. You’ll collaborate closely with world-class researchers and engineers, leveraging Lambda’s compute to optimize model and system performance.

Our interns work hands-on across two complementary tracks, Fundamental Research and Applied Research, depending on their interests and experience.

What You’ll Work On

• Foundation Models, Multi-Modal, Agents

• System benchmarking and performance optimization

Track 1: Fundamental Research

• Research in foundation models for language, vision, life sciences and robotics.

• Multi-modal research, including building efficient data and evaluation toolkits.

• Publish findings in top-tier ML Research conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV/ECCV, ACL, SIGGRAPH), and/or as technical blogs, public datasets, benchmarks, and open-source tools.

Track 2: Applied Research

• Maximize training and inference performance for large-scale AI systems.

• Systematic model and agent evaluation.

• Publish findings in top-tier ML system conferences (e.g. MLSys, OSDI, SOSP, NSDI), and/or as technical blogs, public dataset, benchmarks, and open-source tools.

You

• BS, MS, or Ph.D. student in Computer Science or related field, focusing on Machine Learning.

• Demonstrated project experience or publications in relevant areas.

• Proficient in PyTorch or similar frameworks.

• Strong communication and collaboration skills.

Nice to Have

• Contributions to open-source machine learning projects.

• Experience with foundation models, multi-modal, agentic systems.

• Experience with dataset creation, evaluation design, or system benchmarking.

• Experience optimizing model efficiency or scaling ML workloads.

Visit Lambda’s research page for more information about our work and opportunities: https://lambdalabs.com/research

Salary Range Information

This is an hourly role, eligible for overtime. The hourly rate for this position has been set based on market data and other factors. However, a hourly rate higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.

About Lambda

• Founded in 2012, ~400 employees (2025) and growing fast

• We offer generous cash & equity compensation

• Our investors include Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, US Innovative Technology, Gradient Ventures, Mercato Partners, SVB, 1517, Crescent Cove.

• We are experiencing extremely high demand for our systems, with quarter over quarter, year over year profitability

• Our research papers have been accepted into top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG

• Health, dental, and vision coverage for you and your dependents

• Wellness and Commuter stipends for select roles

• 401k Plan with 2% company match (USA employees)

• Flexible Paid Time Off Plan that we all actually use

A Final Note:

You do not need to match all of the listed expectations to apply for this position. We are committed to building a team with a variety of backgrounds, experiences, and skills.

Equal Opportunity Employer

Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.