Research Engineer

About the Company

Human Archive is a research lab backed by Y Combinator focused on modeling human embodied intelligence. Founded by Stanford and UC Berkeley researchers, we build custom hardware products and publish research to recover human embodied intelligence as a learned model.

Responsibilities

• Evaluate how different sensor modalities impact VLA training and downstream robotics performance
• Work across RGB-D video, IMUs, motion capture, tactile sensing, audio, and wearable systems data
• Design experiments around synchronization, calibration, fusion, and multimodal alignment
• Prototype quickly and iterate from real-world robotics deployments and research feedback
• Collaborate closely with hardware, ML, and research teams on next-generation sensing systems

Requirements

• Master’s or PhD in robotics, computer vision, sensing systems, or related fields
• Published research in sensor fusion, perception systems, multimodal datasets, or embodied AI
• Strong technical intuition around hardware systems and robot learning
• Experience with RGB-D video, IMUs, motion capture, tactile sensing, or robotics systems
• Experience with reinforcement learning and real-world robot deployments
• Highly curious and execution-oriented mindset