Senior Learning Perception Engineer - SLAM

• Lead the design, development, and optimization of perception and SLAM pipelines for humanoid robots, including visual-inertial odometry, mapping, localization, object detection, tracking, segmentation, pose estimation, and scene understanding.
• Develop multi-sensor fusion frameworks integrating 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., IsaacSim) with real-world datasets to enhance model generalization and robustness.
• Contribute to best practices in code quality, model versioning, reproducibility, and deployment.

• 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 CV / multi-modal libraries such as OpenCV, Detectron2, YOLO, and foundation models for perception and language (e.g., SAM, CLIP, DINOv2, Flamingo).
• 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) under compute, latency, and thermal constraints.
• Track record of shipping ML/Perception or SLAM systems from R&D into production robotics platforms.

• Experience with humanoid robots, bipedal locomotion, and manipulation tasks.
• Experience with modern SLAM frameworks (e.g., ORB-SLAM, VINS, Rtabmap, GTSLAM, Cartographer) or learning-based SLAM systems.
• Strong classical computer vision skills (geometry-based methods, feature extraction) complementing learning-based approaches.
• Expertise in model acceleration, quantization, or compression (TensorRT, ONNX Runtime).
• Familiarity with real-time frameworks and middleware such as ROS 2, GStreamer, or zero-copy pipelines.
• Knowledge of synthetic data generation and domain adaptation techniques for training perception and SLAM models.
• Contributions to open-source robotics or vision software stacks.

• Prolonged periods of sitting at a desk and working on a computer
• Must be able to lift 15 pounds at times
• Vision to read printed materials and a computer screen
• Hearing and speech to communicate

The annual salary range is $190,000 - $235,000

*This is a direct hire.

Please, no outside Agency solicitations.

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