Humanarchive
Machine Learning Engineer
San Francisco
Sponsorship not specifiedDetected 74 days ago
Machine LearningComputer VisionRoboticsResearch
About 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.
- 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.
Responsibilities
- Build systems for multimodal perception, annotation, dataset QA, and robotics evaluation
- Develop tooling for benchmarking, observability, and temporal efficiency
- 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.
- To achieve this, we build custom hardware products, deploy them globally at scale, and publish research.
- We are building the infrastructure to accelerate that transition by assembling the Human Archive mafia.
- You will own meaningful systems from day one and see your work directly impact model capabilities.
Requirements
- Experience with video understanding, tracking, pose estimation, robotics, or real-world sensor systems
- Strong technical intuition and ability to move quickly in ambiguous research environments
Benefits
- 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.
- Build post-training and reinforcement learning systems around robotics failure modes and corrective demonstrations
- Strong ML engineering fundamentals across robotics, computer vision, and perception systems
Company info
- Our mission is to recover human embodied intelligence as a learned model.
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