> Markdown version of [/jobs/ext/3985752-staff-robotics-software-engineer-amr-autonomy](https://www.wearedevelopers.com/jobs/ext/3985752-staff-robotics-software-engineer-amr-autonomy). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Robotics Software Engineer, AMR Autonomy - **Company:** Tesla Motors - **Location:** Austin, TX, United States - **Contract:** Permanent contract - **Skills:** Computer Vision, C++ (Programming Language), CANopen, Software Debugging, Linux, Kinematics, Motion Planning, Posix, Regression Testing, OPC Unified Architecture, Sensor Fusion, Software Engineering, Systems Integration, Robot Operating System, Mobile Robots, Transfer Learning, Grpc, Lidar - **Published:** October 28, 2026 - **Apply:** https://jobs.localjobnetwork.com/apply/add/88727991/1 ## About the Role * Experience diagnosing localization failures in real environments: repetitive geometry, changing layouts, dynamic obstacles, sensor degradation, timing jitter * Strong C++ (17/20) and Linux; concurrent, performance-sensitive software development. Go experience for service-level integration * Solid foundations in robotics math: coordinate transforms, probabilistic estimation (EKF/UKF/PF), numerical optimization, mobile-robot kinematics/dynamics * Practical navigation, motion planning, trajectory tracking, and closed-loop control experience, with intuition for how sensor latency and localization uncertainty affect physical behavior * Experience integrating sensors, PLCs, motor controllers, and embedded systems; debugging across hardware-software boundaries (e.g., gRPC, POSIX IPC, CAN/CANopen, OPC UA) * Sound architectural judgment, clear cross-functional communication, and ability to lead implementation while staying hands-on * Plus: industrial AMRs, automated forklifts, or manufacturing automation; ROS 2, Nav2, physics-based-simulation; experience applying learned models to improve perception or control in deployed systems (e.g., sim-to-real transfer, neural cost maps, learned obstacle detection) ## Description We are seeking a hands-on technical lead to own the autonomy and motion-control stack for our autonomous mobile robots (AMRs). You will write production software spanning SLAM, localization, navigation, trajectory planning, and vehicle control - enabling robots to navigate dynamic factory environments, dock precisely with equipment, and recover reliably from failures. You will lead technical decisions, mentor engineers, and work directly with hardware and factory teams from development through deployment. What You'll Do * Own onboard autonomy architecture: perception, state estimation, planning, control, and the interfaces between them * Develop SLAM, localization, and sensor-fusion algorithms (LiDAR, odometry, IMUs, vision); solve calibration, map maintenance, and relocalization * Integrate 3D perception and depth estimation for robust obstacle avoidance of low-profile, complex, and negative obstacles * Build navigation and motion planning for dynamic factory environments using deterministic orchestration (e.g., Behavior Trees) for docking, constrained maneuvers, and multi-tier recovery * Develop trajectory generation, kinematic/dynamic models, and vehicle control across payload ranges and drive configurations (differential, swerve, omni) * Define clean interfaces with fleet management: translate orchestration commands into predictable robot behavior with execution status, telemetry, and recovery * Build simulation, regression testing, and log-replay pipelines to validate localization accuracy and robustness at scale * Diagnose edge-case failures on deployed robots; improve diagnostics, observability, and self-healing to minimize manual intervention * Explore opportunities to augment classical pipelines with learned models (neural cost maps, learned dynamics, sim-to-real transfer) where they measurably improve robustness or reduce hand-tuning * Lead design reviews, set engineering standards, mentor engineers, and drive work from problem definition through verified production results What You'll Bring * Deep expertise in SLAM and localization: implemented or substantially extended algorithms for scan matching, graph optimization, state estimation, sensor fusion, or loop closure * Track record shipping autonomy software on robots in sustained 24/7 production - not just demos or research