Staff Autonomy/Robotics Engineer

We’re hiring a Senior Autonomy Engineer specializing in VIO/VI-SLAM to work directly with our CTO improving our vision-based indoor autonomy stack. Our drones and robots help warehouses manage inventory , powered by our state-of-the-art autonomy engine. They operate 24x7 without any human intervention, running every day in customer warehouses and factories around the country.

We're looking for someone who loves early-stage startups, working on a small and close-knit engineering team, and can help lead complex projects from start to finish. If you are interested in working on challenging visual-inertial localization problems which form the basis for safety-critical autonomy -- with rapid and continuous feedback from a fleet of field-deployed robots -- this role is for you!

We’re Corvus Robotics , a Y Combinator and VC-backed startup, building robots that help warehouses and factories automate inventory visibility. We built Corvus One, the world’s first infrastructure-free, fully autonomous warehouse drone system. We have large customer contracts waiting for us to fulfill, are comfortably funded, and have clear metrics to hit next year for the next round. We sell logistics robotics, AI software, and data-driven supply chain insights to dozens of customer facilities in North America.

This is an opportunity to join a core team building for one of the world's largest markets for indoor robotics: inventory management. Warehouses touch every physical object around you, from the personal items you own to the building itself, and inventory management is a core process every warehouse and factory does globally. You should have at least several years of experience putting visual-inertial localization (VIO/VISLAM) systems onto production robots or resource-constrained edge devices (e.g AR/VR headsets, mobile phones), architecting and implementing ideas which go beyond academic state-of-the-art, and mentoring and helping lead a small team.

Performance engineering, SIMD-oriented programming (SSE, AVX)

PyTorch or other deep-learning training frameworks

Intel OpenVINO or other deep-learning inference acceleration frameworks

Experience with PX4 or similar deeply-embedded middleware, or bare-metal embedded systems

BS in Computer Science, Aerospace/Aeronautics, Robotics or similar (NOT a requirement)