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Waymo

Senior Research Scientist, AI Foundations Recipes

Waymo is hiring a Senior Research Scientist, AI Foundations Recipes in Oxford and London, United Kingdom. It pays £123k-£129k a year and Level rates it ; you can apply on Waymo.

Level's read on this job

  • On Level's scale, this research scientist role is Builds AI ●●●●: the job is building AI systems.
  • Some of the work can be done remotely, according to the posting.
  • The posting mentions PyTorch, TensorFlow and JAX among its tools and skills.
  • Level classes it as a senior role.
  • Waymo has 365 other open roles on Level.

AI in this role

Lead foundational machine learning research and data mixture strategies for autonomous driving foundation models at Waymo.

PyTorchTensorFlowJAXPython
fine-tuningmachine-learningdeep-learningreinforcement-learninggenerative-modelingbayesian-inferencedistributed-training

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’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.

The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of 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. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.

In this hybrid role, you will report to a Senior Staff Software Engineer.

You will:

  • Partner with foundation model training teams to determine optimal data mixtures, training curricula, objectives, and other design choices that shape model capabilities.
  • Design global-scale pipelines for dynamically updating and reusing data mixtures as our understanding of model behavior evolves and real-world datasets are continually ingested.
  • Develop and deploy principled data-selection algorithms (e.g. influence estimation, proxy models, gradient similarity search) to find targeted subsets of data for fine tuning and RL.
  • Run large-scale empirical studies linking pre-training data composition to downstream post-training performance, translating those scaling laws into optimized production training runs.
  • Collaborate closely with behavior, perception, and evaluation teams to test these foundation models and measure their impact on the performance of the Waymo Driver.

You have:

  • PhD in ML or related in AI/CS, or MSc with a strong academic publication record
  • Strong statistical / ML knowledge
  • Proficiency in Python
  • 3+ years of experience with modern deep learning frameworks: JAX, TensorFlow/PyTorch

We prefer:

  • Proven track record of deploying ML models to production environments
  • Deep learning experience, especially with generative models, e.g., LLMs/VLMs, and/or reinforcement learning or imitation learning, transformer models, autoencoders and embeddings
  • Autonomous driving experience
  • C++ experience

The expected base salary range for this full-time position 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. 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£123,000—£129,000 GBP

How we rate this

Senior Research Scientist, AI Foundations Recipes at Waymo rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Fine-tuningMachine learningDeep learningReinforcement learningGenerative ModelingBayesian InferenceDistributed TrainingPyTorch

Also common in research scientist jobs at this level

Pay

Typical research scientist job
$192k

Use the typical research scientist figure as a reference when pay comes up. See research scientist jobs

Questions you could be asked

  1. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  2. Tell me about a project where machine learning was part of your work. What did you do?
  3. Tell me about a project where deep learning was part of your work. What did you do?
  4. Tell me about a project where reinforcement learning was part of your work. What did you do?
  5. Tell me about a project where generative modeling was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Fine-tuning, Machine learning, Deep learning, Reinforcement learning, and Generative Modeling. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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