Principal AI/ML Engineer

Responsibilities

• Define and drive the technical vision and architecture for trajectory generation systems used in autonomous driving.
• Lead the development of ML-based trajectory generation models capable of handling complex and dynamic driving environments.
• Architect scalable training pipelines using large-scale driving datasets and simulation environments.
• Guide the integration of trajectory generation models into real-time onboard systems with strict latency and safety requirements.
• Influence the design of next-generation embodied AI architectures for driving.
• Mentor senior engineers and help develop the next generation of technical leaders.
• Raise the bar for engineering excellence, modeling rigor, and production-quality systems.
• Foster a culture of innovation, ownership, and collaborative problem solving.
• Lead complex technical initiatives spanning multiple teams across the autonomous driving stack.
• Collaborate closely with teams working on: data, perception, simulation, safety validation, onboard systems.
• Define roadmaps and priorities aligned with product milestones and safety goals.
• Drive solutions from research prototypes through production deployment.
• Your Skills & Abilities:
• MS or PhD in Computer Science, Robotics, Machine Learning, or related field.
• Experience leading technical teams delivering production ML systems.
• Deep expertise in one or more areas: robotics planning and control, imitation learning or reinforcement learning, generative models, large-scale machine learning systems
• Strong software engineering skills (Python, C++, or similar).
• Experience deploying ML models into real-world or safety-critical environments.
• Demonstrated ability to define architecture and drive large technical initiatives across teams.

Requirements

• Experience with autonomous driving, robotics, or embodied AI systems.
• Background in trajectory planning, motion planning, or behavior modeling.
• Experience with large-scale training infrastructure and distributed ML pipelines.
• Experience with simulation-based training or evaluation of driving policies.
• Remote/Hybrid: This role is based remotely but if you live within a 50-mile radius of Austin, Detroit, Warren, Milford or Mountain View, you are expected to report to that location three times per week, at minimum.
• Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of the California Bay Area.
• The salary range for this role is $296,300.00 to $423,900.00. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
• Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
• Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident

Benefits

Additional Information

Job Description Job Description At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We're turning today's impossible into tomorrow's standard -from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale. We are looking for a Principal Technical Lead Manager (TLM) to lead the Trajectory Generation team within the Embodied AI organization. This role combines deep technical leadership in machine learning and robotics with people leadership and organizational impact. Trajectory generation is one of the most critical components of an autonomous driving system. It is responsible for producing the precise vehicle motion plans that determine how the car moves through the world - lane changes, merges, turns, yielding, obstacle avoidance, and complex interactions with other road users. Every decision ultimately manifests as a trajectory executed by the vehicle. As the leader of this team, you will shape the algorithms and ML systems that translate sensor inputs into safe, smooth, and human-like driving behavior across diverse real-world scenarios. You will lead a high-performing team of engineers building ML-driven trajectory generation systems, and drive the roadmap that takes these models from research to production deployment on vehicles. This role requires someone who can set technical direction, mentor senior engineers, and lead large cross-functional initiatives, while remaining deeply involved in the technical architecture and modeling strategies.

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