Senior Perception Learning Engineer

Job description

Job responsibilities

• Lead Design, develop, and optimize perception and SLAM pipelines for humanoid robots, including visual-inertial odometry, mapping, localization, object detection, tracking, segmentation, pose estimation, and scene…
• Develop multi-sensor fusion frameworks that integrate cameras, LiDAR, depth sensors, and IMUs for robust real-time state estimation and mapping in dynamic human-centered environments.
• Contribute to scalable data pipelines, training infrastructure, and inference frameworks to accelerate model development, evaluation, and deployment.
• Drive research and deployment of learning-based models for SLAM, 3D scene understanding, and perception optimized for humanoid locomotion, manipulation, and human-robot interaction.
• Implement performance profiling, regression testing, and telemetry systems to ensure perception and SLAM modules meet strict latency, accuracy, and reliability requirements on edge devices.
• Collaborate with planning, control, and hardware teams to define perception-to-action interfaces, ensuring real-time compatibility with locomotion and manipulation pipelines.
• Guide the integration of synthetic data (e.g., simulation frameworks like IsaacSim) with real-world datasets to enhance model generalization and robustness.
• Contribute to best practices in code quality, model versioning, reproducibility, and deployment.

Job requirements

• MS/PhD in Computer Science, Robotics, Computer Engineering, or related field.
• 3- 5+ years building and shipping perception and/or SLAM systems in robotics or real-time vision applications.
• Strong background in SLAM, VIO, probabilistic state estimation, and deep learning for computer vision.
• Practical expertise in detection, segmentation, multi-object tracking, 3D perception, and learning-based mapping/localization.
• Hands-on experience with modern AI frameworks (PyTorch, JAX, TensorFlow) and computer vision / multi-modal libraries such as OpenCV, Detectron2, YOLO, and foundation models for perception and language (e.g., SAM, CLIP,…
• Proficiency in Python and modern C++, with strong software engineering fundamentals (version control, testing, CI/CD).
• Deep understanding of 3D geometry, camera models, and probabilistic estimation (EKF/UKF, factor graphs, SLAM, VIO).
• Experience deploying optimized perception or SLAM models on edge hardware (GPU/NPU/embedded platforms) under compute, latency, and thermal constraints.