{"schemaVersion":"jobsearcher.job.v1","id":"5eb9d4180583137cf39fd6fc","url":"https://jobsearcher.com/jobs/5eb9d4180583137cf39fd6fc","canonicalUrl":"https://jobsearcher.com/jobs/5eb9d4180583137cf39fd6fc","title":"Computer Vision & Autonomy Engineer","description":"As a Computer Vision & Autonomy Engineer, you will be joining the team responsible for the design, development, and implementation of high-speed perception and autonomy stacks capable of identifying and tracking highly dynamic objects. You will solve the unique challenges of high-dynamic sensing, where relative velocities are extreme and the margin for error is zero.Key ResponsibilitiesPerception Pipeline Development: Develop robust real-time Deep Learning and Classical CV algorithms for classification, and tracking (e.g., YOLO, Transformer-based architectures) of highly dynamic objects. High-Speed State Estimation: Implement Visual-Inertial Odometry (VIO) and filtering techniques to estimate target 3D trajectories and \"Time-to-Go\" under high-G maneuvers. GPS denied perception stack: Create \"GPS-denied\" navigation solutions and anti-jamming vision pipelines that maintain autonomy when external signals are compromised. Guidance Logic: Design \"Vision-Based Pursuit\" laws and Proportional Navigation (PN) enhancements that translate visual target states into actionable steering commands. Real-time Deployment: Optimize algorithms for ultra-low latency execution on low-power devices, ensuring the \"sensor-to-actuator\" delay is minimized. Deterministic Benchmarking: Profile and eliminate \"long-tail\" latency spikes in the autonomy stack to ensure a deterministic sensor-to-actuator response time. Required QualificationsEducation: Master’s or PhD in Robotics, Computer Science, or Aerospace Engineering with a focus on Computer Vision or Autonomous Systems. Dynamic Vision skills: Expert knowledge of object tracking (KCF, SORT, DeepSORT) and the geometry of moving camera platforms. Real-Time Software: Proficiency in C++20 and CUDA for high-throughput image processing, and Python for training ML models. Mathematics: Deep understanding of 3D geometry, Kalman Filtering (EKF/UKF), and the physics of relative motion. Preferred SkillsEO/IR camera: Experience working with Long-Wave Infrared (LWIR) or Mid-Wave Infrared (MWIR) sensors. Embedded Systems: Experience deploying models on NVIDIA Jetson Orin or FPGA-based vision processing. High-Fidelity Simulation: Proficiency in NVIDIA Isaac Sim, Unreal Engine 5, or Gazebo to generate synthetic data for rare \"corner-case\" scenarios. Control Integration: Understanding of how perception latency affects the stability of flight control loops.Compensation Range: $80K - $150K","company":"Arxlight","rawCompany":"arxlight","city":"Oakland","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-04-24T13:08:40.058Z","occupations":[{"code":"17-2199.08","title":"Robotics Engineers","slug":"robotics-engineers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541330","title":"Engineering Services","slug":"engineering-services"},{"code":"541715","title":"Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)","slug":"research-and-development-in-the-physical-engineering-and-life-sciences-except-nanotechnology-and-biotechnology"},{"code":"334511","title":"Search, Detection, Navigation, Guidance, Aeronautical, and Nautical System and Instrument Manufacturing","slug":"search-detection-navigation-guidance-aeronautical-and-nautical-system-and-instrument-manufacturing"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Computer Vision & Autonomy Engineer","description":"As a Computer Vision & Autonomy Engineer, you will be joining the team responsible for the design, development, and implementation of high-speed perception and autonomy stacks capable of identifying and tracking highly dynamic objects. You will solve the unique challenges of high-dynamic sensing, where relative velocities are extreme and the margin for error is zero.Key ResponsibilitiesPerception Pipeline Development: Develop robust real-time Deep Learning and Classical CV algorithms for classification, and tracking (e.g., YOLO, Transformer-based architectures) of highly dynamic objects. High-Speed State Estimation: Implement Visual-Inertial Odometry (VIO) and filtering techniques to estimate target 3D trajectories and \"Time-to-Go\" under high-G maneuvers. GPS denied perception stack: Create \"GPS-denied\" navigation solutions and anti-jamming vision pipelines that maintain autonomy when external signals are compromised. Guidance Logic: Design \"Vision-Based Pursuit\" laws and Proportional Navigation (PN) enhancements that translate visual target states into actionable steering commands. Real-time Deployment: Optimize algorithms for ultra-low latency execution on low-power devices, ensuring the \"sensor-to-actuator\" delay is minimized. Deterministic Benchmarking: Profile and eliminate \"long-tail\" latency spikes in the autonomy stack to ensure a deterministic sensor-to-actuator response time. Required QualificationsEducation: Master’s or PhD in Robotics, Computer Science, or Aerospace Engineering with a focus on Computer Vision or Autonomous Systems. Dynamic Vision skills: Expert knowledge of object tracking (KCF, SORT, DeepSORT) and the geometry of moving camera platforms. Real-Time Software: Proficiency in C++20 and CUDA for high-throughput image processing, and Python for training ML models. Mathematics: Deep understanding of 3D geometry, Kalman Filtering (EKF/UKF), and the physics of relative motion. Preferred SkillsEO/IR camera: Experience working with Long-Wave Infrared (LWIR) or Mid-Wave Infrared (MWIR) sensors. Embedded Systems: Experience deploying models on NVIDIA Jetson Orin or FPGA-based vision processing. High-Fidelity Simulation: Proficiency in NVIDIA Isaac Sim, Unreal Engine 5, or Gazebo to generate synthetic data for rare \"corner-case\" scenarios. Control Integration: Understanding of how perception latency affects the stability of flight control loops.Compensation Range: $80K - $150K","datePosted":"2026-04-24T13:08:40.058Z","dateModified":"2026-04-24T13:08:40.058Z","hiringOrganization":{"@type":"Organization","name":"Arxlight","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Oakland","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"5eb9d4180583137cf39fd6fc"},"url":"https://jobsearcher.com/jobs/5eb9d4180583137cf39fd6fc"}}