Senior Perception Learning Engineer

Join Apptronik, a leading robotics company dedicated to improving human quality of life and addressing the labor shortage. As a Senior Perception Learning Engineer, you will lead the research and development of advanced perception systems for humanoid robots. Your work will focus on cutting-edge research in perception, SLAM, object detection, world modeling, and multi-sensor fusion. You will collaborate with various teams, mentor junior engineers, and contribute to shaping Apptronik's long-term perception and autonomy roadmap.

• Lead the design, development, and optimization of perception pipelines for humanoid robots, including object detection, tracking, segmentation, pose estimation, and scene understanding.
• Develop multi-sensor fusion frameworks that integrate cameras, LiDAR, depth sensors, and IMUs for robust real-time perception in dynamic human-centered environments.
• Architect and maintain scalable data pipelines, training infrastructure, and inference frameworks to accelerate model development, evaluation, and deployment.
• Hearing and speech to communicate
• This role requires balancing research innovation with practical engineering to deliver deployable, high-performance perception stacks
• Experience deploying optimized models on edge hardware (GPU/NPU/embedded platforms) under compute, latency, and thermal constraints
• MS/PhD in Computer Science, Robotics, Computer Engineering, or related field
• Proficiency in Python and modern C++, with strong software engineering fundamentals (version control, testing, CI/CD)
• Strong background in deep learning for computer vision, with practical expertise in detection, segmentation, multi-object tracking, and 3D perception
• Track record of shipping ML/Perception systems from R&D into production robotics platforms
• Deep understanding of 3D geometry, camera models, and probabilistic estimation (EKF/UKF, SLAM, VIO)
• 3-5+ years of experience building and deploying perception systems for robotics, autonomous vehicles, or real-time vision applications
• 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, DINOv2, Flamingo)
• Experience with humanoid robots, bipedal locomotion, and manipulation tasks
• Expertise in model acceleration, quantization, or compression (TensorRT, ONNX Runtime)
• Strong classical computer vision skills (geometry-based methods, feature extraction) complementing deep learning approaches
• 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 models
• Contributions to open-source robotics or vision software stacks
• Must be able to lift 15 pounds at times
• [Prolonged periods of sitting at a desk and working on a computer
• Vision to read printed materials and a computer screen