About the Role:
Lead perception engineering for a defense technology team developing autonomous systems to detect and track aerial threats. You will own the perception domain and work closely with robotics, controls, and hardware engineers to deliver reliable capabilities on real-world equipment.
What You'll Do:
Design perception architecture spanning detection, tracking, classification, and sensor fusion.
Develop computer vision models and training pipelines, then deploy them on-device.
Fuse EO/IR and other relevant sensor data across the perception stack.
Optimize real-time performance for embedded hardware and tight latency budgets.
Partner with robotics, controls, and hardware teams to make practical system design decisions.
Mentor perception engineers while contributing hands-on technical work.
What We're Looking For:
At least 5 years of experience building and shipping perception systems on real hardware.
Strong Python and C++ skills, with experience developing production machine learning models and end-to-end training-to-deployment pipelines.
Hands-on experience building real-time computer vision detection and tracking from live sensor data, and personal ownership of perception models or tracking systems.
Experience deploying models on-device with TensorRT, ONNX, or equivalent, and optimizing for embedded compute and latency constraints.
Relevant experience in defense, autonomy, robotics, or aerospace, with a track record of systems that perform in real-world conditions.
Experience with aerial target tracking, moving-camera compensation, EO/IR or other sensor fusion, thermal imagery, or small and long-range targets is valuable.
Radar or RF perception, classified programs, sensor fusion in challenging environments, and mentoring experience are also useful.
A degree in computer science, electrical engineering, robotics, or a related field, or equivalent practical experience.
Compensation & Benefits:
Base salary is $190,000 to $222,000 USD annually. Visa sponsorship is not available.
Location: On-site in San Francisco, California, United States.
