Senior Perception Engineer

Job description

Job responsibilities

• Design, train, and optimize deep learning models for detection, segmentation, segmentation, pose estimation, and classification — with a focus on real-world robustness over benchmark performance.
• Build low-latency inference pipelines that approach real-time performance; profile and optimize models for deployment on embedded and edge hardware.
• Develop and improve multi-object tracking algorithms for reliable identification and motion prediction of items across frames.
• Solve challenging perception problems specific to food robotics: deformable objects, occlusions, varying lighting, and high visual similarity between categories.
• Own the end-to-end ML lifecycle: data collection strategy, annotation tooling, dataset curation, augmentation pipelines, model training, evaluation, deployment, and field debugging.
• Develop tooling to monitor model performance in production and drive continuous improvement cycles.
• Partner closely with robotics, hardware, and software engineers to translate perception capabilities into reliable end-to-end robot behaviors.
• Help define the perception roadmap and influence technical direction as the team grows.

Job requirements

• BS, MS, or PhD in Computer Science, Robotics, Electrical Engineering, or a closely related field.
• 5+ years of combined research and industry experience in computer vision and machine learning, with a track record of shipping perception systems to production.
• Deep expertise in at least two of: instance/semantic segmentation, object detection, 3D perception, or multi-object tracking.
• Strong Python skills; experience building production-quality, maintainable code — not just research prototypes.
• Hands-on experience with deep learning frameworks (PyTorch strongly preferred) and the full training pipeline from data to deployed model.
• Experience working with RGBD sensors, depth cameras, and point cloud data.
• Proven ability to build and optimize models for low-latency, real-time inference.
• Familiarity with ROS or similar robotics middleware.