About the job
We are seeking highly motivated and talented experienced engineers to join our team to lead the post-training LLM for autonomous driving. You will be working alongside a world-class team of researchers and engineers to develop and advance the next generation of frontier AI models.
Responsibilities
Post-training for instruction following and CoT thinking: Develop and apply methods to enhance the instruction following and CoT abilities of LLM models targeting autonomous driving applications. This may include fine-tuning strategies, reinforcement learning techniques, or novel approaches to improve LLM’s ability to solve complex driving tasks, make decisions, and interact with dynamic environments.
Collaborate deeply with research teams asking the right technical questions, translating research advances into production-ready systems, and shaping joint technical direction.
Provide technical leadership to influence senior engineers and researchers across ML, infra, and data teams.
Raise the technical bar for how Waymo trains, evaluates, and deploys LLM models in the autonomous driving technical stack.
Qualifications
Minimum
Demonstrated experience developing post-training methods for LLM models
Extensive experience with deep learning frameworks (e.g. PyTorch, JAX) and large-scale model training.
A track record of operating effectively under ambiguity, setting direction amid rapidly evolving research and technical constraints
The ability to translate research insights into production-ready post-training pipelines and systems
Experience applying large language models or foundation models in complex, safety-critical domains (e.g., autonomy, robotics, or other high-reliability systems)
Excellent communication and collaboration skills
Preferred
No preferred qualifications listed.