Perception Engineer

Sobre el puesto

About the company Our client is a technology company. The role Raydar is recruiting for this role on behalf of our client. Own and improve a production computer vision service running on embedded hardware, delivering performance and stability gains to a system already in use in the field. The work centers on tuning real-time video and model pipelines and partnering closely with hardware and systems colleagues. What you'll do - Re-architect and optimize an existing real-time perception service so it handles more video streams with better stability. - Evaluate and integrate faster, higher-performing models while keeping real-time performance on edge hardware. - Bring depth estimation capabilities onto embedded compute to support three-dimensional tracking. - Tune the video and inference stack on edge devices to get the most out of the hardware. - Work with hardware and systems engineers to ship perception improvements to deployed systems. Requirements What we're looking for - 4 to 7 years of experience, with strong Python and C++ skills. - Hands-on experience building production perception or machine learning systems, beyond research work. - Familiarity with GPU-accelerated inference tooling and deployment on embedded edge devices. - Prior work applying computer vision within physical, hardware-based products. - Solid grasp of video pipelines and how camera feeds behave in real deployments. - Track record of taking vision models from development into live use, including object tracking across frames. - Ability to own system architecture at a senior level. - Self-directed working style with comfort collaborating across functions in a fast-moving startup. - Bachelor's or master's degree in computer science. Bonus points - Exposure to industries where reliability and safety are critical. Benefits Compensation and benefits - Base salary: USD 220,000 to 270,000 per year - Equity - Health insurance - Retirement plan - Commuter benefits - Family planning benefits Location and work model - San Francisco, CA, United States - Hybrid, 4 days in office - Full-time

Publicada el 29 sept 2026