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# Senior ML Engineer, Perception

- **Company:** CLERA, LLC
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $190,000.0 - $222,000.0
- **Contract:** Permanent contract
- **Skills:** Computer Vision, C++ (Programming Language), Computer Engineering, Python (Programming Language), Machine Learning, Real-Time Operating Systems, Sensor Fusion, Scripting, Robot Operating System, ONNX (Open Neural Network Exchange) Format, TensorRT
- **Published:** October 31, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-ml-engineer-perception-san-francisco-ca--095953dc-0ddd-4bbe-b03a-7826b1fa8433

## About the Role

Computer Engineering, Robotics Software, Embedded Hardware, Budgeting, Realtime Operating System, Robotics, Mentoring, Python Programming/Scripting Language, Engineering, C++ Programming Language, * At least 5 years building and shipping perception systems on physical hardware.

 * Production ML engineering experience in Python and C++, including model development, training pipelines, and deployment.
 * Hands-on experience building real-time computer vision detection and tracking from live sensor data, and shipping systems for real-world targets.
 * Experience deploying models on-device with TensorRT, ONNX, or equivalent, and optimizing for embedded compute and latency constraints.
 * A recent background in computer vision, perception, robotics software, or related machine learning for physical systems.
 * Experience with multi-sensor fusion, EO/IR or thermal imagery, moving-camera compensation, or small and long-range targets is valuable.
 * Counter-UAS, aerial tracking, radar or RF perception, classified programs, and work in adversarial or denied environments are also relevant.

## Description

Lead the perception stack for an autonomous defense technology system, owning detection, tracking, classification, and sensor fusion. You will work closely with robotics software, controls, and hardware engineers to deliver perception that performs reliably in real-world conditions., * Design and own perception architecture across detection, tracking, classification, and sensor fusion.

 * Develop ML models and training pipelines, then deploy them on embedded devices.
 * Fuse EO/IR and other sensor data across the targeting system.
 * Optimize perception software for real-time performance on embedded hardware and within tight latency budgets.
 * Partner with robotics, controls, and hardware teams to align perception capabilities with system constraints.
 * Mentor perception engineers as the team grows.