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Senior Perception Learning Engineer

Apptronik· Software Engineering
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Sunnyvale, CA$220k - $250kDirect hirePosted 1w ago

About the role

Senior Perception Learning Engineer at Apptronik focusing on developing and deploying perception, SLAM, and multi-sensor fusion systems for humanoid robots, with emphasis on real-time performance, edge deployment, and integration with planning, control, and hardware teams.

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 understanding.
  • 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.

Qualifications

  • 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, 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 platforms) under compute, latency, and thermal constraints.
  • Track record of shipping ML/Perception or SLAM systems from R&D into production robotics platforms.

Skills

Required:Perception and SLAM pipelinesMulti-sensor fusionDeep learning for visionEdge deploymentProgramming
Last updated Oct 18, 2026. Interested? Apply on the company site.

About Apptronik

One Platform for the Future of Work

Apptronik designs humanoid robotics platforms with mobility, manipulation, and human-centered interaction to support people in the workplace.

3PLApolloApollo for ManufacturingApollo for RetailApollo for WarehouseBuilt for the Real WorldForm That Fits the WorkGoods-to-Person
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