Research Scientist, RL for Autonomous Planning & World Modeling (AI)

TL;DR

Research Scientist, RL for Autonomous Planning & World Modeling (AI): Researching and developing RL and distillation techniques for autonomous vehicle trajectory planning with an accent on foundation world models and post-training evaluation. Focus on integrating emerging AI research into internal infrastructure and scaling high-impact ML methods.

Location: Hybrid (Mountain View, San Francisco, New York City, Kirkland). Must be based in the US.

Salary: $204,000—$259,000 USD

Company

hirify.global is an autonomous driving technology company building the hirify.global Driver to improve mobility and safety through fully autonomous ride-hailing services.

What you will do

• Participate in hirify.global’s Foundation World Model post-training and evaluation.
• Research and develop cutting-edge RL and distillation techniques for Autonomous Vehicle Trajectory Planning.
• Integrate emerging research from the AI community into internal RL infrastructure through rigorous ablations.
• Partner with cross-functional engineering and research teams to scale post-training best practices.

Requirements

• PhD or Masters in Computer Science, Machine Learning, Robotics, or a similar technical field.
• 3+ years of industry or post-doc research experience in Reinforcement Learning or Foundation Models.
• Demonstrated original contributions via high-impact publications (NeurIPS, ICLR, CVPR) or significant open-source work.
• Proficiency in implementing scalable, distributed model training flows (Data parallel, FSDP, and other sharding approaches).
• Willingness to work with the complexity of globally distributed inference infrastructure.

Nice to have

• PhD with a research focus on RL, Foundation Models, or Multi-Modal learning.
• Experience designing and deploying RL infrastructure, specifically for on-policy learning or alignment with human preferences.
• First-author publications at top-tier AI venues.
• Experience with many-machine training infrastructure and tensor-parallel inference techniques.

Culture & Benefits

• Discretionary annual bonus program.
• Equity incentive plan.
• Generous company benefits program.
• Opportunity to collaborate with other research teams across Alphabet.