
About Waymo
Revolutionizing transportation with autonomous driving
Key Highlights
- Operates in cities like Phoenix, San Francisco, and LA
- Completed over 10 million fully driverless rides
- Raised $11.1 billion in funding
- Aiming for one million trips per week by 2026
Waymo, a subsidiary of Alphabet Inc., is at the forefront of autonomous driving technology, operating robotaxis in cities like Phoenix, San Francisco, and Los Angeles. With over 10 million fully driverless rides and more than 100 million miles driven, Waymo is transforming transportation. The compan...
🎁 Benefits
Waymo offers comprehensive medical, dental, and vision insurance for employees and their dependents, along with commuter benefits and onsite wellness ...
🌟 Culture
Waymo fosters a culture of innovation and safety, focusing on the real-world application of autonomous technology. The company values diversity and in...
Skills & Technologies
Overview
Waymo is seeking a Staff Machine Learning Engineer to develop scalable systems for training and fine-tuning generative models. You'll work with Python, TensorFlow, and PyTorch to enhance the Waymo Driver's performance. This role requires expertise in machine learning and reinforcement learning techniques.
Job Description
Who you are
You have extensive experience in machine learning, particularly in developing and implementing scalable systems for training large-scale generative models. Your background includes a strong proficiency in Python, TensorFlow, and PyTorch, allowing you to create innovative solutions that enhance driving behaviors. You are familiar with reinforcement learning algorithms and have a solid understanding of reward functions and training paradigms tailored for high-fidelity evaluations.
You thrive in collaborative environments, working closely with researchers and software engineers to drive performance improvements across technology stacks. Your analytical mindset enables you to combine expert human judgment with advanced machine learning models, delivering valuable insights and training data for various metrics and components.
You are passionate about the potential of autonomous driving technology and are motivated by the mission to improve access to mobility while saving lives. You understand the importance of safety and reliability in autonomous systems and are committed to developing solutions that meet these standards.
Desirable
Experience with simulation workflows and insight tools is a plus, as is familiarity with large-scale data processing and evaluation systems. You are open to exploring new machine learning techniques and are eager to contribute to the ongoing development of the Waymo Driver.
What you'll do
In this role, you will lead the implementation and iteration of novel reinforcement learning algorithms, focusing on generating insightful driving behaviors. You will build scalable systems that facilitate the training and fine-tuning of generative models, ensuring they produce realistic driving scenarios. Your work will directly impact the Waymo Driver's ability to navigate complex environments safely and efficiently.
You will collaborate with cross-functional teams to enhance the evaluation and developer onboarding journeys, leveraging your expertise to improve the overall performance of the Waymo Driver. Your contributions will help shape the future of autonomous driving technology, making it more reliable and accessible to users.
You will also engage in research activities, exploring new methodologies and techniques that can be applied to the development of machine learning systems. Your insights will be invaluable in refining existing processes and driving innovation within the team.
What we offer
Waymo offers a competitive salary range of £150,000—£162,000 GBP, along with eligibility for an annual bonus program and equity incentive plan. You will be part of a mission-driven company that values collaboration and innovation, working alongside some of the brightest minds in the industry. We encourage you to apply even if your experience doesn't match every requirement, as we believe diverse teams build better products.
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