2 months ago
Mountain View, CA, USAStaff+
Base Salary
$240k - $265k/yr
Responsibilities
- Lead the integration of learned models into the behavior planning stack.
- Collaborate with ML teams on model improvements, requirements, evaluation, and deployment.
- Develop learned planning components and ML-driven planning signals for behavior classification, actor intent understanding, and data-driven decision-making.
- Design hybrid integration strategies combining learned components with heuristic planning systems.
- Define validation, fallback, monitoring, and safety criteria for learned planning components.
- Debug and analyze model behavior using simulation, logs, metrics, and real-world autonomy data.
- Partner with Perception, ML, Planning, Simulation, Systems, and Safety teams.
- Lead technical designs and mentor other engineers.
Requirements
- Strong experience in autonomous vehicles, robotics, or a related autonomy domain.
- Deep technical background in behavior planning, decision-making, or motion planning.
- Strong software engineering skills with proficiency in C++; Python proficiency is a plus.
- Experience with heuristic or classical planning systems.
- Experience integrating or developing learned behavior policies, behavior classification, trajectory prediction, or actor intent models.
- Ability to reason about safety, system behavior, evaluation, and deployment risk.
- Excellent cross-functional communication and technical leadership skills.
Benefits
- Base salary range of $240,000–$265,000 USD for the SF/Silicon Valley location.
- Total compensation includes base pay, equity, bonus, and a competitive benefits package.
- Kodiak promotes a diverse, safe, collaborative, and equal-opportunity work environment.
- Visa sponsorship may be provided for eligible candidates, subject to applicable restrictions.
Categories
ML EngineeringRobotics
