Senior Autonomous Vehicle Planner Engineer

Helm.ai builds AI software for autonomous driving and robotics. Our "Deep Teaching" methodology is uniquely data and capital efficient, allowing us to surpass traditional approaches. Our unsupervised learning software can train neural networks for L2/L3 autonomy, which drastically reduces the need for human annotation and is hardware-agnostic. We work with some of the world's largest automotive manufacturers towards mass production and we've raised over $100M from Honda, Mando, and others to help us scale.

You will:

• Architect core behavior planning: Own the logic and decision frameworks that guide the vehicle through complex maneuvers (like unprotected turns, dynamic merges, and yielding).

• Optimize trajectories: Develop robust trajectory generation systems that perfectly balance safety, passenger comfort, and vehicle progress.

• Ensure verifiable safety: Translate complex traffic rules and operational design domain (ODD) constraints into interpretable, highly safe planning behaviors.

• Solve the long-tail: Tackle exciting, real-world edge cases, from unpredictable pedestrians and occlusions to complex construction zones.

• Drive cross-functional integration: Collaborate closely to seamlessly connect your planner with perception, prediction, localization, and control modules.

• Test and validate: Prove out your solutions through rigorous scenario-based simulations, closed-course trials, and live on-road testing.

• Optimize for real-time: Deliver robust, highly deterministic performance tailored for embedded automotive hardware.

You have:

• MS/PhD in robotics, Computer science, Electrical Engineering, or equivalent industry experience.

• Solid C++ for robust, real-time systems, paired with Python for tooling and data analysis.

• Deep familiarity with both planning algorithms (search, sampling and optimization-based) and complex decision architectures (like FSMs and behavior trees).

• A solid grasp of vehicle kinematics and dynamics to ensure safe, smooth, and realistic motion profiles.

• Hands-on experience with ROS/ROS2 or comparable autonomous middleware.

The following are not required but a plus:

• Experience shipping a planner on public roads and analyzing real-world disengagement data.

• Hands-on experience with tools like CARLA or custom in-house scenario frameworks.

We offer:

• Competitive health insurance options

• 401K plan management

• Remote-friendly and flexible team culture

• Free lunch and fully-stocked kitchen in our South Bay office

• Additional perks: monthly wellness stipend, office set up allowance, company retreats, and more to come as we scale

• The opportunity to work on one of the most interesting, impactful problems of the decade