At a Glance
- Tasks: Develop and optimise machine learning systems for autonomous driving technology.
- Company: Waymo, a leader in autonomous driving innovation.
- Benefits: Competitive salary, bonus program, equity incentives, and generous benefits.
- Why this job: Join a mission-driven team to revolutionise mobility and save lives.
- Qualifications: M.S. or Ph.D. in relevant fields with 5+ years of ML experience.
- Other info: Collaborative environment with opportunities for impactful projects and career growth.
The predicted salary is between 120000 - 130000 £ per year.
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 DUE ML Core London team builds and operates scalable machine learning systems, simulation workflows, and insight tools designed to improve the evaluation and developer onboarding journeys. By combining expert human judgment with advanced machine learning models, we deliver training and evaluation data for hundreds of metrics and components that comprise the Waymo Driver.
We are looking for researchers and software engineers passionate about developing ML techniques for evaluation systems and driving performance improvements across our technology stack. You will:
- Build scalable systems for training and fine-tuning large-scale generative models to produce realistic and evaluate interesting driving behaviors.
- Lead the implementation, and iteration of novel RL algorithms, reward functions, and training paradigms tailored for generating high-fidelity and insightful driving behaviors.
- Lead the development of cutting-edge Deep Learning models and Generative AI (LLM/VLM) solutions to enhance human-led triaging, introduce automation for high-volume workflows, and perform nuanced analysis of self-driving behavior to detect critical anomalies.
- Oversee the production and optimization of machine learning models aiming to assess Waymo’s expansive fleet of vehicles that cumulatively travel millions of miles.
- Proactively monitor and assimilate best practices from within Alphabet and the broader industry to develop a novel Reinforcement Learning from Human Preference (RLHF) based data collection and evaluation system.
- Collaborate closely with multiple teams (e.g., Prediction, Planning, Research), other technical leads, and senior leaderships across Waymo to deliver on key strategic efforts.
You have:
- M.S. or Ph.D. degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent practical experience.
- 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.
- Strong publication record or history of impactful project delivery in RL or related areas.
- Proficiency in Python and standard ML frameworks (e.g., JAX, TensorFlow).
- Experience with large-scale distributed training and data processing.
- Proven ability to lead complex and ambiguous technical projects from conception to completion.
We prefer:
- 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.
- Experience designing and using metrics for evaluating complex AI systems.
- Track record of technical leadership, influencing senior stakeholders, and driving innovation across team boundaries.
- Excellent communication skills, with the ability to articulate complex technical concepts clearly.
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 £120,000 — £130,000 GBP
Machine Learning Engineer in London employer: Waymo
Contact Detail:
Waymo Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Waymo. LinkedIn is your best mate here—send personalised messages and ask for a chat about their experiences. You never know who might put in a good word for you!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to reinforcement learning or autonomous systems. Share it during interviews or even on your LinkedIn profile to catch the eye of recruiters.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and ML concepts. Practice common algorithms and be ready to discuss your past projects in detail. We recommend using platforms like LeetCode or HackerRank to sharpen your skills.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the team at Waymo. Let’s get you that dream job!
We think you need these skills to ace Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with ML models, especially in Reinforcement Learning, and don’t forget to mention any relevant projects or publications that showcase your skills.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about autonomous driving technology and how your background aligns with Waymo's mission. Be sure to mention specific experiences that relate to the job description.
Showcase Your Technical Skills: When filling out your application, make sure to highlight your proficiency in Python and any ML frameworks you’ve worked with, like JAX or TensorFlow. Mention any experience with large-scale distributed training and data processing as well!
Apply Through Our Website: We encourage you to apply through our website for the best chance of being noticed. It’s straightforward and ensures your application goes directly to the right team. Plus, we love seeing candidates who take the initiative!
How to prepare for a job interview at Waymo
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts, especially reinforcement learning and deep learning. Be ready to discuss your past projects and how you've applied these techniques in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare to tackle some technical problems during the interview. Think through your approach to developing scalable systems or optimising models, and be ready to explain your thought process clearly.
✨Familiarise Yourself with Waymo's Mission
Understand Waymo's goals and how their technology works. Being able to relate your skills and experiences to their mission of improving mobility and safety will show your genuine interest in the role.
✨Communicate Clearly
Practice articulating complex technical concepts in a simple way. You’ll likely need to explain your ideas to non-technical stakeholders, so being clear and concise is key to making a good impression.