About the Role
The role involves designing, implementing, and optimizing machine learning systems that enable intelligent decision-making in complex driving environments, with a focus on learned planning and reinforcement learning methodologies.
Responsibilities
- Design and train machine learning models for vehicle planning systems
- Apply reinforcement learning techniques to real-world driving scenarios
- Develop algorithms that improve decision-making under uncertainty
- Collaborate with cross-functional teams to integrate ML solutions into vehicle software
- Optimize model performance for low-latency inference in production environments
- Evaluate model behavior using large-scale simulation and real-world data
- Improve training pipelines for scalability and reproducibility
- Work with sensor data to inform planning decisions
- Conduct experiments to validate safety and reliability of learned policies
- Refine reward functions to align with driving objectives
- Debug and analyze model failures in edge cases
- Implement robustness checks for policy generalization
- Contribute to versioning and deployment of ML models
- Stay current with advancements in reinforcement learning research
- Translate research concepts into production-grade code
- Support testing and validation across diverse geographic regions
- Ensure compliance with safety and performance standards
- Document technical approaches and system architecture
- Mentor junior engineers in machine learning best practices
- Participate in code and design reviews
Nice to Have
- PhD in machine learning, robotics, or related discipline
- Publications in top-tier conferences (e.g., NeurIPS, ICML, CoRL)
- Experience with offline reinforcement learning
- Knowledge of imitation learning techniques
- Background in control theory or optimal control
- Experience with multi-agent reinforcement learning
- Familiarity with formal verification methods for ML systems
- Contributions to open-source ML projects
- Industry experience in autonomous vehicles or drones
Compensation
Competitive salary and benefits package
Work Arrangement
Hybrid work model with flexibility for remote and on-site collaboration
Team
Collaborative engineering team focused on advancing autonomous driving systems
About the Team
This role is part of a dedicated group advancing the intelligence layer of autonomous driving, focusing on enabling vehicles to make safe, efficient, and adaptive decisions in dynamic environments.
What We Value
Technical excellence, iterative development, safety-first mindset, collaboration, and a passion for solving real-world challenges in autonomy.
