Machine Learning Engineer, AI Foundations @ Waymo
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About Waymo
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Originally started as the Google Self-Driving Car Project in 2009, Waymo has evolved to power the Waymo Driver – The World's Most Experienced Driver™ – that enhances mobility and saves lives.
About the Role: Machine Learning Engineer, AI Foundations
The AI Foundations team is focused on developing machine learning solutions to solve open problems in autonomous driving. These solutions help achieve safe operations in various cities and under diverse driving conditions. This role is based in the Oxford or London, UK office and operates in a hybrid work modality reporting to a Sr. Staff Machine Learning Engineer.
Key Responsibilities
- Design, train, and evaluate large-scale ML models for autonomous systems.
- Frame real-world challenges as defined ML problems using deep, reinforcement, and imitation learning.
- Scale ML approaches to handle Google-sized data pipelines and execute in real-time.
- Collaborate with ML infrastructure, data science, systems engineering, and research teams including Waymo Research, Google Brain, and DeepMind.
Qualifications
- Strong programming skills in Python, JAX, and TensorFlow/PyTorch.
- Solid background in statistics and machine learning.
Preferred Skills
- C++ experience.
- ML infrastructure experience with scaling training and evaluation processes.
- Deep learning expertise, particularly in generative models and reinforcement/imitation learning.
- Experience in autonomous driving.
Compensation & Benefits
This full-time role offers a base salary ranging from £72,000 to £78,000 GBP along with participation in bonus programs, equity plans, and a comprehensive benefits package.
Key skills/competency
Machine Learning, AI, Reinforcement Learning, Deep Learning, Imitation Learning, Python, TensorFlow/PyTorch, JAX, Autonomous Driving, ML Infrastructure
How to Get Hired at Waymo
🎯 Tips for Getting Hired
- Research Waymo's culture: Review mission, projects, and employee experiences.
- Tailor your resume: Highlight ML, Python, and autonomous driving skills.
- Demonstrate technical expertise: Present relevant ML project work and case studies.
- Prepare for interviews: Focus on problem-solving, technical deep dives, and collaboration.