Research Engineer, Vision

Job Description

Research Engineer Computer Vision & Machine Learning

Want to build vision systems that let machines understand the physical world as naturally as we do

This role sits within a highly technical team developing a new class of computing devices where perception language and interaction are tightly integrated. Vision is a core capability. Your work will directly influence how machines see reason about space and collaborate with humans in real-world environments.

Youll join a specialist vision group working across 3D computer vision and machine learning. The problems sit at the boundary between learned models and physical reality including gaze tracking SLAM multi-camera geometry and systems that explicitly model optics refraction and light transport. The focus is on geometry-aware physically grounded approaches rather than purely pixel-driven modelling.

This is a hands-on research engineering role. Youll move between reading papers building and training models designing datasets running controlled experiments and deploying onto real hardware. Youll work closely with firmware and hardware teams to ensure models operate reliably on-device.

Your work will include:

• Developing ML models across 3D perception tracking and spatial understanding

• Designing model architectures training pipelines evaluation frameworks and inference systems

• Working with large-scale multi-camera and sensor-rich datasets

• Translating state-of-the-art research into robust production-ready systems

• Creating new approaches when existing methods do not meet performance or physical constraints

Youll have genuine technical ownership. The team values clear thinking strong experimental discipline and the ability to make informed bets on promising ideas.

Youll likely bring end-to-end experience building computer vision and ML models alongside strong familiarity with modern research in 3D or geometry-aware vision. Hands-on experience with PyTorch or JAX is expected as is comfort working with complex datasets. The ability to operate independently in ambiguous environments is important as is clear communication across research hardware and product teams.

A Bachelors degree or higher in computer science machine learning computer vision applied mathematics or a related field is required. A Masters or PhD is a plus particularly if youve worked on geometry-aware or physically informed modelling approaches. Experience deploying ML systems into real products or working in high-ownership startup environments would be valuable.

Compensation: $190000 - $320000 base (depending on experience) equity
Benefits: 401(k) matching 100% employer-paid health vision and dental insurance unlimited PTO and sick time medical FSA matching
Location: San Francisco on-site collaboration required

If youre motivated by building geometry-aware vision systems that connect AI to the physical world in meaningful ways wed like to hear from you!

All applicants will receive a response.