Principal AI/ML Engineer
Job Summary
General Motors is seeking a Principal Technical Lead Manager to lead the Trajectory Generation team within the Embodied AI organization. This role involves defining technical vision, leading the development of machine learning-based trajectory generation models for autonomous driving, and mentoring senior engineers. The successful candidate will drive solutions from research prototypes through production deployment to ensure safe and human-like driving behavior.
Responsibilities
- Define technical vision and architecture for trajectory generation systems
- Lead development of ML-based trajectory generation models
- Architect scalable training pipelines using large datasets and simulation
- Mentor senior engineers and foster a culture of innovation
- Collaborate across cross-functional autonomous driving teams
Required Skills
- MS or PhD in Computer Science, Robotics, Machine Learning, or related field
- Experience leading technical teams delivering production ML systems
- Expertise in robotics planning, reinforcement learning, or generative models
- Strong software engineering skills in Python or C++
- Experience deploying ML models into real-world or safety-critical environments
Job Details
Job Description
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.
What You'll Do:
- 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.
Preferred Qualifications:
- 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.
Compensation & Benefits:
- The salary range for this role is $296,300.00 to $423,900.00.
- Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
- Benefits: Medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.
- Relocation: This job may be eligible for relocation benefits.
- Company Vehicle: Eligible to participate in a company vehicle evaluation program.