Machine Learning Engineer, AI Foundations
Machine Learning Engineer, AI Foundations

Machine Learning Engineer, AI Foundations

Full-Time 55800 - 70000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Join a creative team to design and evaluate cutting-edge machine learning models for autonomous driving.
  • Company: Waymo, a leader in autonomous driving technology with a mission to improve mobility and safety.
  • Benefits: Competitive salary, bonus program, equity incentives, and generous benefits.
  • Why this job: Make a real impact on the future of transportation while working with top-tier tech teams.
  • Qualifications: Strong programming skills in Python and experience with machine learning frameworks.
  • Other info: Hybrid work schedule with opportunities for collaboration across leading research teams.

The predicted salary is between 55800 - 70000 £ 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 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.

This role follows a hybrid work schedule and you will report to a Senior Staff Software Engineer.

Responsibilities

  • Work with a creative team of people who help to design, train, and evaluate the large-scale ML models that are used throughout Waymo’s systems, both onboard autonomous vehicles and offboard in simulation.
  • Frame open-ended real-world problems as well-defined ML problems; develop and apply cutting-edge ML approaches (deep learning, reinforcement learning, imitation learning, etc) to these problems; scale them to Google-sized data pipelines; and streamline them to run in real-time on the cars.
  • Collaborate with other teams including the ML infrastructure, data science and systems engineering teams, as well as various research teams such as Waymo Research, Google Brain, DeepMind and academia.

Qualifications

  • Good programming skills - Python, JAX, TensorFlow/PyTorch
  • Strong statistical / ML theoretical knowledge, and practical experience

Preferred qualifications

  • ML infra experience: training, evaluating and deploying ML models at scale
  • Deep learning experience, especially with generative models, e.g., LLMs/VLMs, and/or reinforcement learning or imitation learning
  • Autonomous driving experience

Compensation

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 £93,000—£100,000 GBP

Machine Learning Engineer, AI Foundations employer: Waymo

Waymo is an exceptional employer, offering a dynamic work environment where innovation meets purpose in the field of autonomous driving technology. With a strong focus on employee growth and collaboration, team members have the opportunity to work alongside leading experts from Alphabet and engage in cutting-edge machine learning projects that directly impact mobility solutions. The hybrid work model and comprehensive benefits package further enhance the appeal of joining Waymo, making it a rewarding place for those passionate about advancing AI and safety on the roads.
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Contact Detail:

Waymo Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Machine Learning Engineer, AI Foundations

✨Tip Number 1

Network like a pro! Reach out to folks in the industry, especially those at Waymo or similar companies. A friendly chat can open doors and give you insights that job descriptions just can't.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's a GitHub repo or a personal website, let your work speak for itself. We love seeing what you've done!

✨Tip Number 3

Prepare for interviews by practising common ML questions and coding challenges. Get comfortable explaining your thought process and how you tackle problems. Remember, it's not just about getting the right answer but how you approach it!

✨Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for passionate candidates who want to join our mission at Waymo.

We think you need these skills to ace Machine Learning Engineer, AI Foundations

Python
JAX
TensorFlow
PyTorch
Machine Learning
Deep Learning
Reinforcement Learning
Imitation Learning
Generative Models
Statistical Knowledge
ML Model Training
ML Model Evaluation
Data Pipeline Scaling
Real-Time Systems

Some tips for your application 🫡

Show Off Your Skills: When you're writing your application, make sure to highlight your programming skills in Python, JAX, and TensorFlow/PyTorch. We want to see how your experience aligns with the role, so don’t hold back on showcasing your ML theoretical knowledge and practical experience!

Tailor Your Application: Take a moment to tailor your application specifically for the Machine Learning Engineer position. Mention any relevant projects or experiences that relate to reinforcement learning, generative modeling, or autonomous driving. This helps us see how you fit into our mission at Waymo.

Be Clear and Concise: Keep your application clear and to the point. Use straightforward language to explain your past experiences and how they relate to the responsibilities of the role. We appreciate clarity, and it makes it easier for us to understand your journey!

Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about Waymo and what we do!

How to prepare for a job interview at Waymo

✨Know Your ML Fundamentals

Brush up on your machine learning theories and concepts, especially those related to deep learning and reinforcement learning. Be ready to discuss how you've applied these in real-world scenarios, as this will show your practical experience and understanding of the field.

✨Showcase Your Coding Skills

Since programming is key for this role, practice coding in Python, JAX, and TensorFlow/PyTorch. You might be asked to solve a problem on the spot, so being comfortable with these languages will help you shine during the technical part of the interview.

✨Prepare for Problem-Solving Questions

Expect to frame open-ended problems as well-defined ML challenges. Think about how you would approach real-world issues in autonomous driving and be prepared to discuss your thought process and the methodologies you would use to tackle them.

✨Collaborate and Communicate

This role involves working with various teams, so demonstrate your ability to collaborate effectively. Share examples of past teamwork experiences and how you communicated complex ideas to non-technical stakeholders, as this will highlight your interpersonal skills.

Machine Learning Engineer, AI Foundations
Waymo

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