Research Scientist, RL for Autonomous Planning

Neura Market; Mountain View, Northern (CA, KY); Hybrid; USD 204,000 - 259,000; Full time

Benefits offered by this job

Health insurance

401(k) with company match

Paid time off 20 days/year

Sick time 40 hours/year

Holidays 13 days/year

Job summary

Waymo in Mountain View, CA is seeking a senior researcher to advance foundation models and reinforcement learning for autonomous driving systems. You will contribute to world model post-training, evaluation, and integration with production RL infrastructure.

The role emphasizes scalable training, distributed inference, and collaboration with cross-functional teams to push state-of-the-art in autonomous vehicle AI, with a competitive compensation package and comprehensive benefits.

Qualifications

• PhD or Masters in Computer Science, ML, Robotics or related field with 3+ years of RL/Foundation Models experience.
• Demonstrated high-impact publications or major open-source contributions.
• Experience implementing scalable model training flows and distributed inference infrastructure.

Responsibilities

• Participate in Waymo’s Foundation World Model post-training and evaluation.
• Research and develop RL and Distillation techniques for Autonomous Vehicle Trajectory Planning.
• Integrate research into Waymo’s RL infrastructure and run rigorous ablations.
• Collaborate with engineering and research teams to share best practices.

Skills

Reinforcement learning

Foundation models

Multi-Modal learning

Distributed training

Inference infrastructure

Education

PhD or Masters in Computer Science/Machine Learning/Robotics

Tools

Data parallel

Fully Sharded Data Parallel (FSDP)

Tensor parallel

Job description

Waymo in Mountain View, CA is seeking a senior researcher to advance foundation models and reinforcement learning for autonomous driving systems. You will contribute to world model post-training, evaluation, and integration with production RL infrastructure.

The role emphasizes scalable training, distributed inference, and collaboration with cross-functional teams to push state-of-the-art in autonomous vehicle AI, with a competitive compensation package and comprehensive benefits.