Dexmate

Dexmate

Senior robotics navigation engineer

Santa Clara Office · Senior

Sponsorship not specifiedDetected 276 days ago
C++AlgorithmsRoadmappingRoboticsElectrical EngineeringSensorsResearch

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About the role

  • You are not prototyping algorithms in simulation - you are deploying them on hardware, validating them in real environments, and owning their reliability at scale.
  • We want engineers who have closed that loop before:
  • on self-driving cars, AGVs, mobile robots, or similar deployed autonomous systems.

Responsibilities

  • Design, implement, and deploy production-grade 3D SLAM and localization systems fusing data from LiDAR, RGB-D cameras, IMUs, wheel encoders, and proprioceptive signals
  • Build and maintain state estimation pipelines - Kalman Filters, Extended Kalman Filters (EKF), Unscented Kalman Filters (UKF), or Factor Graph backends (GTSAM, Ceres, g2o) - with reliable accuracy in dynamic, GPS-denied, and perceptually degraded environments
  • Develop real-time 3D navigation algorithms: costmap generation from point clouds, global and local path planners (sampling-based, optimization-based), and traversability analysis
  • Implement sensor calibration pipelines (intrinsic and extrinsic) for multi-sensor rigs
  • own the calibration quality that underpins system accuracy
  • Design and build the evaluation and regression frameworks that prove the navigation stack is working correctly - logging, metrics, replay tooling, and failure analysis infrastructure
  • Collaborate with perception, controls, and hardware teams to integrate the navigation stack end-to-end into the full robot autonomy system
  • own root cause analysis and system-level fixes when localization or navigation breaks in deployment
  • Implement sensor calibration pipelines (intrinsic and extrinsic) for multi-sensor rigs; own the calibration quality that underpins system accuracy

Requirements

  • 5+ years of industry experience in robotics autonomy, with a primary focus on SLAM, localization, or state estimation
  • Proven track record of deploying navigation or SLAM systems on real autonomous platforms - self-driving vehicles, AGVs, mobile robots, or equivalent - not just simulation or research prototypes
  • Hands-on experience with 3D SLAM modalities: LiDAR SLAM, Visual SLAM (VSLAM), Visual-Inertial Odometry (VIO), or multi-modal fusion
  • Proficiency in C++ (C++14/17 or newer) for real-time, performance-critical code
  • Experience with optimization libraries: GTSAM, Ceres Solver, g2o, or equivalent factor graph backends
  • Familiarity with ROS/ROS 2 and standard robotics tooling
  • Ability to explain why a localization module failed in a specific scenario to both a technical peer and a non-technical stakeholder

Nice to have

  • M.S. or Ph.D. in Robotics, Computer Science, Electrical Engineering, or related field
  • Background in semantic SLAM or scene understanding - associating geometric maps with object-level semantics
  • Experience with GPU acceleration (CUDA) for perception or navigation pipelines
  • GNSS/RTK fusion experience for outdoor or GPS-blended deployments
  • Prior experience in a startup or fast-moving R&D environment with an emphasis on shipping
  • Contributions to open-source SLAM or navigation frameworks (ORB-SLAM, RTAB-Map, Cartographer, LIO-SAM, KISS-ICP, etc.)
  • Familiarity with map management at scale: map storage, versioning, sharing across a robot fleet, and lifecycle management

Company info

  • Our mission is to democratize robotics by lowering the barrier to entry, delivering a plug-and-play platform for developers, researchers, and enterprises, and cultivating an open ecosystem that accelerates the evolution of physical AI.
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