Brief Summary
Join a high-impact engineering team building robust computer vision capabilities for advanced robotic systems used in real-world production environments.
You will take algorithms from prototyping through deployment, focusing on accuracy, reliability, and real-time performance.
Responsibilities
Design and develop computer vision algorithms for detection, recognition, tracking, and scene understanding.
Build and maintain software modules that integrate vision algorithms into robotics platforms with strong performance and reliability.
Implement and improve 3D perception pipelines, including multi-view geometry, depth estimation, and 3D reconstruction workflows.
Develop and refine calibration solutions (camera intrinsic, multi-camera, and robot-to-camera) suitable for production use.
Optimize algorithms and code for runtime efficiency, accuracy, and real-time execution (including GPU acceleration where applicable).
Prototype new approaches, evaluate feasibility, and move solutions from concept to deployment with cross-functional partners.
Create test plans and validation methods to ensure stable behavior across varied operating conditions.
Produce clear technical documentation covering design choices, implementation details, and verification results.
Stay current with evolving computer vision and machine learning techniques and apply relevant advances to improve solutions.
Requirements
Master’s or PhD in Computer Science, Electrical Engineering, Robotics, or a related discipline.
5+ years of industry experience delivering computer vision solutions in applied, production-facing environments.
Strong fundamentals in computer vision and image processing (e.g., filtering/denoising, feature/edge-based methods) and applied machine learning for vision systems.
Hands-on experience with calibration methods and deploying calibration workflows in real systems.
Proficiency in C++ and Python; experience with CUDA and performance engineering is preferred.
Practical familiarity with common vision/3D tooling (e.g., OpenCV, point cloud processing libraries) and ML frameworks (e.g., TensorFlow or PyTorch).
Experience with 3D reconstruction concepts and implementation (e.g., modern neural rendering / 3D representation approaches).
Strong problem-solving skills, ability to work cross-functionally, and comfort communicating complex technical topics clearly.
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