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source · wttj·req · jb_3856a6a1c5·listed 2d ago

Machine Learning Engineer

Waymo·London, United Kingdom·Hybrid·Full-time
Sourced listing · wttjSalary disclosed
Posted
13 May 2026
via wttj
Type
Full-time
Arrangement
Hybrid
United Kingdom
Deadline
14 June 2026
closes in 30d
compensation · disclosed
£120,000 — £130,000
source · wttj

Summary

the pitch

Join Waymo, the leading autonomous driving technology company. As a Machine Learning Engineer, you will build and operate scalable machine learning systems, develop cutting-edge deep learning models, and collaborate with multiple teams to deliver key strategic efforts. Enjoy a comprehensive benefits package, including medical, dental, and vision insurance, competitive compensation, and a hybrid work model.

Role

posted by company
  • We are looking for researchers and software engineers passionate about developing ML techniques for evaluation systems and driving performance improvements across our technology stack
  • M.S. or Ph.D. degree Computer Science, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent practical experience
  • Experience with large-scale distributed training and data processing
  • Proficiency in Python and standard ML frameworks (e.g., JAX, TensorFlow)
  • 5+ years of hands-on experience in developing and applying Machine Learning models, with a significant focus on Reinforcement Learning
  • Demonstrated expertise in deep learning, sequence modeling, and generative models
  • Proven ability to lead complex and ambiguous technical projects from conception to completion
  • Strong publication record or history of impactful project delivery in RL or related areas
  • 7+ years of relevant experience in ML/RL research and application
  • Experience in the autonomous vehicles domain, robotics, or complex simulation environments
  • Deep understanding of state-of-the-art RL techniques, including those used for fine-tuning large models (e.g., from human feedback/preferences)
  • Familiarity with large-scale simulation platforms and their integration with ML training workflows
  • Track record of technical leadership, influencing senior stakeholders, and driving innovation across team boundaries
  • Experience designing and using metrics for evaluating complex AI systems
  • Excellent communication skills, with the ability to articulate complex technical concepts clearly