Distinguished Engineer, Trajectory Generation
We are building a nationwide L3/L4-capable driverless product that is safe, comfortable, and robust across diverse U.S. highway conditions — all under strict real‑time and onboard‑compute constraints.
As Distinguished Robotics Engineer for Trajectory Generation, you will own the technical vision, architecture, and quality bars for the planning stack from sensors to trajectories including but not limited to a modern ML planner with multi-stage training. You will design and ship real‑time planners that meet tight latency and compute budgets while delivering best‑in‑class safety, comfort, and robustness, and you will set the experimentation standards and roadmap for this critical part of the autonomy system.
What You’ll Do
Planning Architecture & Ownership
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Lead the ML trajectory generation planning stack for nationwide L3, including technical vision, architecture, interfaces, and quality bars.
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Define clear APIs and contracts with perception, localization, mapping, and control teams to ensure reliable end‑to‑end behavior.
Real-Time Trajectory Planning & Safety
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Ensure planning behavior achieves and sustains target KPIs, including intervention rate (MPI), comfort metrics, and reduction in near‑miss collisions (NMC).
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Integrate confidence and distribution‑shift indicators directly into the planning loop so low‑confidence or out‑of‑distribution conditions are surfaced and handled appropriately (e.g., safe fallback, policy adjustments, escalation).
Guided Generative Trajectory Proposals & RL
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Apply reinforcement learning (e.g., GRPO) and related techniques to optimize long‑horizon behavior and sensitivity to nuanced objectives (safety, comfort, efficiency).
Data, Evaluation & Long-Tail Generalization
Technical Leadership & Roadmap Influence
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Act as the technical owner for trajectory generation, setting strategy, experimentation standards, and long‑term roadmap.
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Influence the autonomy roadmap and technical trade‑offs, ensuring planning direction is aligned with product goals, safety requirements, and operational constraints.
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Mentor senior and principal engineers, raising the bar on planning, trajectory generation, and embodied‑AI practices across the organization.
Qualifications
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Experience with uncertainty estimation, distribution shift, and failure analysis, with strong judgment on model vs. data interventions.
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Deep understanding of machine learning foundations and latest AI trends, especially in planning, generative modeling, and RL.
