6 days ago
Base Salary
$220k - $250k/yr
Responsibilities
- 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 understanding.
- Develop multi-sensor fusion frameworks integrating cameras, LiDAR, depth sensors, and IMUs for real-time state estimation and mapping.
- Build scalable data pipelines, training infrastructure, and inference frameworks for model development, evaluation, and deployment.
- Research and deploy learning-based models for SLAM, 3D scene understanding, and perception optimized for locomotion, manipulation, and human-robot interaction.
- Implement performance profiling, regression testing, and telemetry systems for latency, accuracy, and reliability requirements on edge devices.
- Collaborate with planning, control, platform software, systems, and hardware teams to define perception-to-action interfaces.
- Integrate synthetic data from simulation frameworks such as IsaacSim with real-world datasets.
- Contribute to code quality, model versioning, reproducibility, and deployment practices.
Requirements
- MS or PhD in Computer Science, Robotics, Computer Engineering, or a related field.
- 3–5+ years of experience building and shipping perception and/or SLAM systems in robotics or real-time vision applications.
- Strong background in SLAM, visual-inertial odometry, probabilistic state estimation, and deep learning for computer vision.
- Practical expertise in detection, segmentation, multi-object tracking, 3D perception, and learning-based mapping and localization.
- Hands-on experience with PyTorch, JAX, TensorFlow, OpenCV, Detectron2, YOLO, and perception foundation models such as SAM, CLIP, DINOv2, or Flamingo.
- Proficiency in Python and modern C++.
- Deep understanding of 3D geometry, camera models, EKF/UKF, factor graphs, SLAM, and visual-inertial odometry.
- Experience deploying optimized perception or SLAM models on GPU, NPU, or embedded edge platforms under compute, latency, and thermal constraints.
- Track record of shipping ML, perception, or SLAM systems from R&D into production robotics platforms.
- Preferred experience with humanoid robots, bipedal locomotion, manipulation, ORB-SLAM, VINS, Kimera, Cartographer, model acceleration, quantization, compression, ROS 2, GStreamer, zero-copy pipelines, synthetic-data generation, domain adaptation, and open-source robotics or vision software stacks.
Benefits
- Direct-hire position.
- Annual base salary range of $220,000–$250,000.
Categories
ML EngineeringRobotics
About Apptronik
Apptronik designs and manufactures AI-enabled humanoid robots, led by its Apollo platform, to automate tasks alongside people in manufacturing and logistics, with potential use in healthcare and homes. The privately held company is headquartered in Austin, Texas, and grew out of the University of Texas at Austin’s Human Centered Robotics Lab; its team previously worked on NASA’s Valkyrie robot. Apptronik’s business model centers on selling robots and the software and services needed to deploy them in industrial environments.