Team Lead Physical AI

Key Responsibilities : KEY RESPONSIBILITIES Technical Leadership & Systems Integration Lead end-to-end software architecture for mobile robotics platforms — perception, localization/SLAM, navigation, motion control, and safety systems. Own design decisions around ROS/ROS 2 middleware, sensor fusion pipelines, and modular hardware abstraction layers. Act as technical lead for fleet-level coordination and communication interfaces (REST, MQTT, CAN). Set technical direction and coding/architecture standards for the team; review designs and code from other engineers. Physical AI, VLA/VLM & Perception Drive integration of Vision-Language-Action (VLA) and Vision-Language Model (VLM) capabilities into the autonomy stack for tasks such as semantic scene understanding, instruction-conditioned navigation, and object/task-level reasoning. Own the Visual SLAM pipeline (e.g., ORB-SLAM, VINS, RTAB-Map or equivalent) for robust localization and mapping across dynamic, GPS-denied, and visually repetitive warehouse/industrial environments. Evaluate, fine-tune, and productionize foundation-model-based perception and reasoning components, balancing on-robot compute constraints with model accuracy and latency. Integrate and validate AI/ML models in production for localization, obstacle detection, and object/pallet identification. Deployment & Field Reliability Take direct ownership of resolving deployment challenges encountered during customer site rollouts — environmental edge cases, network/connectivity constraints, sensor degradation, and unexpected operational scenarios. Drive the verification & validation (V&V) strategy for autonomous robot behavior across simulated and real environments prior to and during deployment. Design for graceful failure handling and energy-aware shutdown logic to improve field reliability and serviceability. Cross-Functional Collaboration Work closely with product managers and hardware teams to translate customer requirements into scalable, field-deployable solutions. Mentor and grow junior and mid-level engineers; document complex subsystems to support organizational knowledge-sharing. REQUIRED SKILLS & EXPERIENCE 4-6 years of experience in mobile robotics / autonomous systems software, with demonstrated ownership of production AMR deployments. Strong hands-on experience with ROS / ROS 2, including middleware architecture and sensor fusion. Proven experience with Visual SLAM techniques and libraries, and a solid grasp of localization and mapping in real-world, GPS-denied environments. Working knowledge of Vision-Language-Action (VLA) and/or Vision-Language Model (VLM) approaches, and how to integrate foundation-model-based perception into constrained, real-time robotic systems. Practical experience with controllers such as PID, Stanley, or Model Predictive Control (MPC) for motion/velocity control. Demonstrated track record of diagnosing and resolving field/deployment issues in live customer or warehouse environments (not simulation-only experience). Proficiency in Python and C++ for robotics software development; familiarity with OpenCV, NumPy/SciPy, and standard ROS toolchains. Experience with fleet-level communication protocols (REST, MQTT, CAN) and hardware-in-the-loop or simulation-based testing frameworks. Prior experience leading or mentoring a small technical team, or clear readiness to step into a team-lead capacity. EDUCATION Bachelor's/Master’s degree in Engineering (Robotics, Instrumentation, Computer Science, Electronics, or related discipline) required Please share your resumes with