Machine Learning Intern

About Human Archive

Human Archive is a robotics data lab founded by Stanford and UC Berkeley dropouts. We work alongside frontier robotics labs and foundation model research groups to collect large-scale, quality, diverse, multimodal datasets of humans performing everyday tasks across household and industrial environments.

We are lean, technical, and operate at extreme speed, taking on unglamorous and conventionally impossible problems that directly unlock step-function gains in model capability.

The deployment of capable humanoids at scale will permanently redefine human labor. Undesirable physical work will disappear, and human effort will shift toward a new era of abundant creativity. This shift is inevitable, and we are building the infrastructure to accelerate it.

We are assembling the best team to solve the hardest problems in embodied intelligence. You will own meaningful systems from day one and see your work directly impact VLA model capabilities. This is a once-in-a-generation inflection point. If you want to leave your dent on humanity and reshape physical labor markets forever, join us!

About the Role

This role is ideal for an early-career engineer or exceptional dropout who wants real ownership and is interested in possibly joining Human Archive as a founding engineer.

As a Machine Learning Intern, you’ll build the data and ML infrastructure that powers the next generation of safe, intelligent, dexterous, and generalizable robots. You’ll work on in-house Vision-Language-Action (VLA) model benchmarking, annotation software, analytics and data platform products, and multimodal alignment tooling. This is a hands-on role at the intersection of applied machine learning, data infrastructure, and robotics, where your work directly shapes how data is collected, validated, annotated, and converted into high-quality learning signal.

Your mandate is to close the loop between research and data collection by building systems that let us rapidly evaluate new environments, tasks, and sensor modalities through fine-tuning and benchmarking our own VLA models, as well as by building annotation pipelines designed for direct model ingestion. You’ll be expected to ship production-grade systems, make architectural decisions, and own projects end to end.

What We’re Looking For

• Passionate individuals who are deeply mission-driven and have demonstrated ownership in previous work
• Engineers who want their work to directly impact the next frontier of robotic intelligence
• Exceptional dropouts or cracked new grads who are excited about converting this internship into a founding engineer role
• This is not a summer role, we want engineers who can start right now

Please do not reach out to us individually. Do not send emails or DMs. We will personally review every application.