Computer Vision Engineer
Role summary
Seeking a Computer Vision Engineer to design and implement real-time vision systems for advanced tracking and simulation. Responsibilities include developing algorithms for object detection, tracking, and motion analysis using high-speed, multi-camera data. The role involves integrating vision pipelines into embedded and desktop systems, optimizing performance with techniques like multithreading and GPU acceleration, and applying camera calibration and sensor fusion. Collaboration with hardware, firmware, and simulation teams is key. Experience with ML workflows, MLOps tools, and real-time optimization is required, along with strong Python skills and a solid understanding of computer vision fundamentals.
Join a fast-moving team building real-time vision systems that power advanced tracking and simulation technology. In this role, you will design and implement computer vision solutions that track objects and motion using high-speed, multi-camera data in a hardware-integrated environment.
What You’ll Do
- Develop real-time algorithms for object detection, tracking, pose estimation, and motion analysis
- Process high-frame-rate, multi-camera data to generate accurate 3D trajectories and impact insights
- Collaborate with hardware, firmware, and simulation teams to integrate vision pipelines into embedded and desktop systems
- Optimize performance using multithreading, SIMD, and GPU acceleration
- Apply camera calibration, stereo vision, and sensor fusion for precise spatial modeling
- Prototype new concepts, evaluate sensors, and support field testing
- Write clean, testable code with unit and integration testing
- Document algorithms, workflows, and data pipelines
- Support ML workflows including dataset versioning, experiment tracking, and deployment (Azure ML)
- Maintain MLOps tools (e.g., CVAT, training pipelines, evaluation workflows)
Required Qualifications
- Bachelor’s or Master’s in Computer Science, Computer Engineering, Electrical Engineering, or related field
- 3+ years of computer vision experience in real-time, product-focused environments
- Strong Python skills with OpenCV or similar libraries
- Solid understanding of camera geometry, calibration, and lens distortion correction
- Experience with multi-camera systems, stereo vision, or 3D reconstruction
- Knowledge of tracking techniques (optical flow, Kalman filters, background subtraction, deep learning)
- Experience with real-time optimization, parallel processing, or embedded CV deployment
Preferred Qualifications
- C++, PyTorch, or TensorFlow experience
- GPU programming (CUDA/OpenGL)
- Embedded systems or real-time video pipelines
- MATLAB or ROS exposure
- Azure ML (workspaces, compute, experiment tracking)
- Docker and containerized ML workflows
- Azure ML DevOps pipelines for automated training and deployment
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