Machine Learning Engineer
Human Archive, San Francisco
The role
As a Machine Learning Engineer, you’ll work on multimodal perception, VLA training, robotics post-training, and downstream policy evaluation. 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 evaluated.
You’ll help close the loop between research and data collection by fine-tuning VLAs on downstream policy performance and building post-training and reinforcement learning systems around real-world robotics tasks. You’ll be expected to make architectural decisions, own projects end-to-end, and operate in highly ambiguous research environments given the novelty and scale of our multimodal datasets.
Your work will help shape how frontier labs and leading robotics companies train their models, transforming physical labor markets and economies while contributing to broader research into human embodied intelligence.
What you will do
- Build systems for multimodal perception, annotation, dataset QA, and robotics evaluation