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Senior ML Engineer, Perception

Clera · On site, San Francisco, US

190.000 - 222.000 USD / Ano · Publicada em 6 de nov. de 2026

Sobre a vaga

ABOUT THE ROLE Lead perception engineering for a defense technology team developing autonomous systems. You will own the perception stack, from detection and tracking to sensor fusion, and help ensure it performs reliably on real hardware in demanding field conditions. WHAT YOU'LL DO - Set the perception architecture for detection, tracking, classification, and sensor fusion. - Develop ML models and training pipelines, then deploy models to embedded devices. - Fuse EO/IR and other sensor data relevant to the system. - Optimize real-time perception performance for embedded compute and latency constraints. - Work closely with robotics, controls, and hardware engineers to deliver practical system capabilities. - Mentor perception engineers while contributing directly to implementation. WHAT WE'RE LOOKING FOR - At least 5 years building and shipping perception systems on physical hardware. - Strong Python and production C++ skills, with experience in computer vision, detection, and real-time tracking on live sensor data. - Experience deploying ML models on-device with TensorRT, ONNX, or equivalent, and optimizing for embedded compute and tight latency budgets. - Experience building ML training pipelines through deployment and shipping systems tested against real-world targets. - Background in perception, robotics, autonomy, aerospace, or defense systems; research-only or offline-only experience is not a fit. - Helpful experience includes aerial target tracking, moving-camera compensation, thermal imagery, EO/IR or other sensor fusion, radar or RF perception, and small or long-range target detection. - BS, MS, PhD, or equivalent experience in computer science, electrical engineering, robotics, or a related field. COMPENSATION & BENEFITS Base salary: $190,000 to $222,000 annually. Visa sponsorship is not available. LOCATION On-site in San Francisco, California. The role includes field testing.

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