Apptronik
Senior Perception Learning Engineer
Sunnyvale, CA · Senior
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About the role
- We operate at the cutting edge of Applied AI, applying our expertise across the full robotics stack to solve some of society's most important problems.
- You will join a team dedicated to bringing Apollo to market at scale, tackling the complex challenges like safety, commercialization, and mass production to change the world for the better.
- Your work will focus heavily on SLAM, visual-inertial odometry, world modeling, and learning-based perception, alongside object detection and multi-sensor fusion, creating the foundation for robust autonomy in real-world settings.
Responsibilities
- 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.
- 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.
Requirements
- Proficiency in Python and modern C++, with strong software engineering fundamentals (version control, testing, CI/CD).
- Experience deploying optimized perception or SLAM models on edge hardware (GPU/NPU/embedded platforms) 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.
- 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.
Nice to have
- Preferred Experience
Compensation
- The annual salary range is $220,000 - $250,000
Benefits
- Drive research and deployment of learning-based models for SLAM, 3D scene understanding, and perception optimized for humanoid locomotion, manipulation, and human-robot interaction.
- 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.
- Experience with modern SLAM frameworks (e.g., ORB-SLAM, VINS, Kimera, Cartographer) or learning-based SLAM systems.
- Strong classical computer vision skills (geometry-based methods, feature extraction) complementing learning-based approaches.
- Contributions to open-source robotics or vision software stacks.
This listing is sourced directly from Apptronik's careers page and normalized into a canonical job model.