Job brief: 2027 Summer Intern, PhD, Machine Learning - Generative World Models & Controllable Simulation

What JoRoute checked · Checked by JoRoute

• Listed on Waymo's own job board. JoRoute does not take listings from job ads or recruiters.
• First seen by JoRoute 2026-11-07 (1 day ago); last confirmed on the board 2026-11-08.
• The apply link opens careers.withwaymo.com, the address Waymo's board gives for this job.
• No other listing with this title and place on this board in the last 90 days.
• No layoff notices (WARN) under this name in the state files JoRoute reads.

What the listing says · Employer's own words, not checked

• Pay: $85 an hour
• Job type: Not stated
• Where: Mountain View, California, United States · Mountain View (US-MTV-EMF680)
• Posted: 2026-11-06

What the job asks · Employer's own words, not checked

Level: Internship. The title says "Intern".

Conditions

• Note: This will be a hybrid onsite internship position.

Main duties

• Design, implement, and scale controllable generation and test-time compute algorithms, multimodal conditioning, and critic-guided flow/diffusion steering—for…
• Investigate multimodal sensor + semantic latent conditioning, and representation alignment to advance toward holistic world simulation.
• Leverage learned realism critics and agentic autoresearch workflows on large-scale TPU clusters to evaluate closed-loop interactive realism, long-tail scenar…
• Write clean, modular, and well-tested JAX code in core simulation and world-modeling codebases, collaborating closely with researchers across Sim Realism, Fo…
• Currently pursuing a PhD in Computer Science, Machine Learning, Robotics, or a related technical field, with an anticipated graduation date between December …

Lines copied from the posting, not rewritten. "Preferred" or "nice to have" items are not listed as must-haves.

How it compares · Compared by JoRoute from listings

• Across Waymo's 316 open listings, 50% of those with a posting date were first posted more than 60 days ago. How Waymo hires

What nobody outside the employer knows · Not known

• Whether the role is already filled or on hold: employers often leave listings up.
• How many people applied, and who reads the applications.
• Where in the published range an offer would land.

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