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Home›Jobs›Waymo›Staff Machine Learning Engineer, Simulation
Waymo

About Waymo

Revolutionizing transportation with autonomous driving

🏢 Tech👥 1001+ employees📅 Founded 2009📍 Mountain View, CA💰 $11.1b⭐ 3.7
B2CTransportAutomation

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...

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Waymo

Staff Machine Learning Engineer, Simulation

Waymo • London, UK

Posted 3w agoStaffMachine learning engineer📍 London
Apply Now →

Skills & Technologies

PythonTensorFlowKerasAWSDockerSQL

Overview

Waymo is hiring a Staff Machine Learning Engineer to develop scalable machine learning and data systems for autonomous driving technology. You'll work with Python, TensorFlow, and AWS to enhance the Waymo Driver's capabilities. This position requires extensive experience in machine learning and data infrastructure.

Job Description

Who you are

You have a strong background in machine learning and data systems, with at least 5 years of experience in building scalable solutions. Your expertise in Python and frameworks like TensorFlow and Keras allows you to develop advanced models that enhance autonomous driving capabilities. You are familiar with cloud platforms such as AWS and have experience deploying machine learning models in production environments. Your understanding of data infrastructure and SQL enables you to manage and analyze large datasets effectively. You thrive in collaborative environments and enjoy working with cross-functional teams to drive innovation in autonomous technology. You are passionate about improving safety and mobility through advanced machine learning techniques.

Desirable

Experience with simulation technologies and tools is a plus, as is familiarity with Docker for containerization. Knowledge of additional programming languages or frameworks can enhance your contributions to the team. You are open to learning new technologies and methodologies that can improve the Waymo Driver's performance.

What you'll do

In this role, you will lead the development of machine learning models that evaluate the behavior of the Waymo Driver in real-world scenarios. You will work closely with the Driver Understanding and Evaluation team to create metrics that assess driving performance and safety. Your responsibilities will include building and operating scalable machine learning systems and data pipelines that support simulation workflows. You will collaborate with engineers and researchers to improve the evaluation processes and onboard developer journeys, ensuring that the systems you create are efficient and effective. You will also contribute to the technical strategy and methodology used to evaluate the Waymo Driver, combining expert human judgments with advanced machine learning models.

What we offer

Waymo offers a competitive salary range of £150,000—£162,000 GBP, along with participation in an annual bonus program and equity incentive plan. You will have access to a generous benefits program that supports your well-being and professional growth. Join a mission-driven company that is at the forefront of autonomous driving technology, where your work will have a direct impact on improving mobility and safety for millions of people. We encourage you to apply even if your experience doesn't match every requirement, as we value diverse perspectives and backgrounds.

Interested in this role?

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