Research Scientist (World Model Post-Training)
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Salary
$213k – $263k per year
Location
Hybrid (New York, San Francisco, Mountain View, United States)
Seniority
Middle · 3+ years exp
Visa
H-1B filings in 12 months: 331 · for this role: 261 · green card filings: 28
Employment
Full-Time
Confirmed on the employer's own hiring board on Oct 13, 2026. First seen by Alion on Oct 11, 2026. Waymo scores B on the Alion truth index.
Overview
Company
Impact
Profile match
Waymo is an American autonomous driving company that began as the Google self-driving car project in 2009 and became a standalone Alphabet subsidiary in 2016. It operates the largest fully driverless commercial ride-hailing service in the world through the Waymo One app, carrying paying passengers with no human in the vehicle across Phoenix, San Francisco, Los Angeles, Austin and an expanding list of cities. Headquartered in Mountain View, California, the company builds its own sensor suite and the Waymo Driver software stack, integrates them into vehicles from partners such as Jaguar, Zeekr and Hyundai, and also develops autonomous trucking technology.
Backed by Bessemer Venture Partners, Sequoia Capital, Kleiner Perkins
Join Waymo, a leader in autonomous driving technology. As a Research Scientist, you will conduct applied world model research and development, post-train Waymo's world model, design experiments, and present results to peers and leadership. You will also leverage AI to write high-quality code, unit tests, and documentation, and automate workflows. Enjoy a hybrid work model, competitive compensation, and a comprehensive benefits package.
Missions
- Conduct applied world model research and development, including post-training of Waymo’s world model.
- Design and execute experiments to train and evaluate large generative models, and present results to peers and leadership.
- Leverage AI to write high-quality code, unit tests, and documentation, and automate workflows.
Profil recherché
- Masters or PhD in deep learning in generative / world modeling- Experience training large foundational models
- Experience with diffusion / flow matching models
- 3+ years of experience with modern deep learning frameworks (e.g., JAX, TensorFlow 2, Pytorch)
- Experience with reinforcement learning
- Experience with reinforcement learning for diffusion / flow matching models
- Experience with post-training of foundational models
- Experience with distillation
- Experience with autonomous vehicles
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