Waymo

Senior Research Scientist, Foundation Model for Simulation

Waymo$204K — $259K *
Technical Services
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Masters or PhD in deep learning, behavior modeling, or simulation
  • Proficiency in Python programming
  • 3+ years of experience with modern deep learning frameworks (preferably JAX or TensorFlow 2)
  • Experience with generative modeling and large language models (e.g., Gemini, Llama)
  • Familiarity with reinforcement learning techniques and transformer models

Responsibilities

  • Conduct applied foundation model research and development
  • Design experiments to train and evaluate large deep learning models
  • Present research results to peers and leadership
  • Write high-quality code along with unit tests and documentation

Benefits

  • Participation in Waymo's discretionary annual bonus program
  • Equity incentive plan
  • Generous company benefits program
Full Job Description
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver™-to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states.

The mission of the Waymo Applied Research team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of the safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet.

In this hybrid role you will report to a Director of Research.

You will:
  • Conduct applied foundation model research and development
  • Design compelling experiments by training and evaluating large deep learning models
  • Present results to peers and leadership
  • Write high quality code, unit tests, and documentation

You have:
  • Masters or PhD in deep learning in behavior and agent modeling or simulation
  • Proficiency in Python
  • 3+ years of experience with modern deep learning frameworks. Prefer JAX or TensorFlow 2; however, Pytorch is acceptable.

We prefer:

Experience with:
  • Generative modeling
  • LLMs or VLMs (e.g., Gemini, Llama, GPT)
  • Post-training, incl. reinforcement learning
  • Distillation
  • Transformer models
  • Autoencoders and embeddings


The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.

Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.

Salary Range

$204,000-$259,000 USD

About Waymo

Waymo LLC is a self-driving technology development company. It is a subsidiary of Alphabet Inc., the parent company of Google. Waymo develops autonomous driving technology and provides ride-hailing services through its Waymo One program. The company has been testing its self-driving technology on public roads since 2009 and has logged millions of miles of autonomous driving. Waymo has partnerships with several automakers and has been working on developing autonomous trucks for use in logistics.
Learn more about Waymo
Size
2,000 employees
Industry
Founded
2009

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