Research Engineer

The role

You will work on multimodal sensing systems and sensor fusion research for embodied AI and robotics. You will research emerging sensing technologies and study how sensor combinations impact robot learning and policy performance.

What you will do

• 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

Required qualifications

• 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, real-world robot deployments, and how data impacts downstream policy performance

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, the lab builds custom hardware products, deploys them globally at scale, and publishes research.