Software Engineer, Autonomous Vehicles – Motion Planning

Helm.ai

Software Engineer designing core components for autonomous vehicles at Helm.ai. Collaborating on deep learning methodologies for advanced motion planning and decision frameworks.

Posted 7/23/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in vehicle behavior planning, trajectory optimization, and safety verification, with a strong foundation in robotics and real-time systems. Proficient in C++ and Python, with hands-on experience in ROS/ROS2 and scenario-based testing.

Highest-signal resume keywords

C++ ProgrammingPython ProgrammingPlanning AlgorithmsVehicle KinematicsROS/ROS2 Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Real-Time SystemsTrajectory GenerationDecision FrameworksSafety VerificationComplex Maneuvers

Soft Skills

Cross-Functional CollaborationProblem Solving

Tools & Technologies

CARLAScenario Frameworks

Industry Keywords

Autonomous VehiclesOperational Design DomainDisengagement DataSimulation Testing

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.
Experience shipping a planner on public roads and analyzing real-world disengagement data (not required but a plus).
Hands-on experience with tools like CARLA or custom in-house scenario frameworks (not required but a plus).

Benefits

Comp & perks

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