About the role
Make the foundational design decisions that determine how robotics software, AI models, and cloud and edge components fit together, defining the core interfaces and engineering contracts other teams depend on. Architect systems that meet demanding real-world constraints, balancing latency, throughput, compute efficiency, reliability, and cost across cloud and on-robot edge environments. Lead the evaluation and validation strategy that gates what ships, establishing the benchmarks, test approach, and quality bar for autonomy, safety, and task performance across simulation, lab, and field, including safe-autonomy boundaries and human-in-the-loop fallback. Drive the hardest cross-stack technical problems personally, taking on the integration failure modes that emerge where AI models meet production robots, and resolving them through rigorous root-cause analysis of system behavior and field data. Connect classical robotics engineering with modern AI, partnering across foundation-model, perception, manipulation, locomotion, and simulation teams to bring learned capabilities into a common, production-grade platform rather than one-off integrations. Establish the engineering bar for
the team, owning design standards and review practices, leading the consequential technical reviews, and lifting the quality, testability, and operability of the systems that matter most. Multiply
the team's output through technical leadership, mentoring senior and principal engineers and raising the technical ceiling of the organization rather than only its headcount. Track the state of the art across embodied AI, robot learning, robotics middleware, and simulation, and decide deliberately how and when new techniques are incorporated into the platform. Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python Master's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 15+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Demonstrated ownership of a major platform, framework, runtime, or large-scale distributed system used in production by other engineering teams, with accountability for its architecture, reliability, and long-term evolution. Experience with robot learning at scale, including vision-language-action policies, foundation models for robotics, imitation learning, reinforcement learning, or embodied artificial intelligence. Experience deploying and operating robots in the real world at fleet scale, including fleet orchestration, over-the-air update systems, observability, and edge runtime on compute-constrained and intermittently connected hardware. Deep systems-level understanding of how perception, learning, planning, control, simulation, and fleet operations interact in deployed autonomous systems, including the failure modes, latency budgets, and trade-offs that emerge at integration boundaries. Demonstrated ability to lead cross-disciplinary technical efforts spanning robotics hardware, perception, learning, planning, simulation, platform infrastructure, field testing, and artificial intelligence and machine learning teams, and to drive consensus across organizational boundaries. Demonstrated ability to mentor and grow senior and principal engineers and to raise the technical bar of an organization through architecture, review, and direction rather than increasing team size. Experience designing and operating machine learning infrastructure and model serving at scale, including inference optimization, low-latency serving, and the versioning, evaluation, and rollback workflows that production models require. Experience with robotics middleware and autonomy tooling such as Robot Operating System (ROS), Robot Operating System 2 (ROS2), Navigation 2 (Nav2), MoveIt, Robot Visualization (RViz), or Foxglove, and the architectural judgment to know where such frameworks fit in a production platform and where they do not. Experience with large-scale simulation and sim-to-real transfer using Isaac Sim, MuJoCo, Drake, Gazebo, or equivalent, including domain randomization, synthetic data generation, and scenario-based validation. Experience with safety-critical or human-in-the-loop autonomy, including evaluation and governance gates and the trust and security controls that regulated and enterprise customers require. Proficiency in C++ and Python, with a track record of building performant, testable, production-quality robotics or systems software, and the judgment to set engineering standards others follow. Published research, open-source platform leadership, patents, standards contributions, or comparable external technical leadership in robotics, autonomous systems, embodied artificial intelligence, machine learning infrastructure, or physical artificial intelligence platforms is a strong plus.
