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- Tasks: Join our team to create ultra-realistic simulations for autonomous vehicles using cutting-edge machine learning.
- Company: Waymo is a leader in autonomous driving technology, aiming to revolutionize mobility and save lives.
- Benefits: Enjoy a competitive salary, annual bonuses, equity plans, and generous company benefits.
- Why this job: Be part of a world-class team pushing the boundaries of AV simulations while making a real impact.
- Qualifications: 5+ years in applied Deep Learning and coding; experience in production problem-solving and data analysis required.
- Other info: This hybrid role involves collaboration with teams in London, MTV, and Oxford.
The predicted salary is between 87000 - 110000 £ per year.
Waymo is an autonomous driving technology company with the mission to be the 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 One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states.
The Simulator team builds state-of-the-art simulations of realistic environments for the testing and training of the Waymo driver. We use machine learning to model the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists etc.), roads, traffic control systems, and weather. To increase the fidelity and steerability of the simulations, we employ large foundation models, trained on our massive datasets that allow us to quickly setup and rollout multiple scenarios to subject our driver to.
We are planning to set up a team in London UK to work with the teams in MTV and Oxford to build these foundation models out and to integrate them into several evaluation and training products. We are looking for research engineers to work on these exciting problems.
In this hybrid role, you will report to an Engineering Director.
You Will
- Be part of a world class research engineering team to grow the state-of-the-art of ultra realistic AV simulations using foundation models
- Collaborate with teams in Waymo Oxford to use large models to improve sim realism
- Design experiments that push the frontiers of AV simulations
- Develop metrics that measure the realism of simulated worlds
- Train and evaluate large models and integrate them into the simulator and its downstream applications
- Help hire outstanding research engineers from diverse backgrounds
- Be a part of a collaborative research engineering team that takes research ideas and productionizes them
We Prefer
- 5+ years experience in applied Deep Learning
- 5+ years coding and design skills
- Experience solving complex production problems using state-of-the-art ML techniques
- Experience taking research to production
- Expertise in Data Analysis or Data Science
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
£145,000—£157,000 GBP
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Staff Machine Learning Engineer, Simulation employer: The Rundown
Contact Detail:
The Rundown Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Machine Learning Engineer, Simulation
✨Tip Number 1
Familiarize yourself with the latest advancements in machine learning, especially in the context of autonomous vehicles. Understanding how large foundation models are applied in simulations will give you a significant edge during discussions.
✨Tip Number 2
Engage with the Waymo community on platforms like LinkedIn or GitHub. Networking with current employees can provide insights into the company culture and the specific challenges they face, which can be valuable during your interview.
✨Tip Number 3
Prepare to discuss your experience with data analysis and production problems. Be ready to share specific examples of how you've successfully implemented machine learning techniques in real-world applications.
✨Tip Number 4
Showcase your collaborative skills by highlighting past experiences where you worked in diverse teams. Waymo values collaboration, so demonstrating your ability to work well with others will be crucial.
We think you need these skills to ace Staff Machine Learning Engineer, Simulation
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description for the Staff Machine Learning Engineer position at Waymo. Understand the key responsibilities and required skills, especially in applied Deep Learning and coding.
Highlight Relevant Experience: In your CV and cover letter, emphasize your 5+ years of experience in applied Deep Learning and any relevant projects that showcase your ability to solve complex production problems using state-of-the-art ML techniques.
Showcase Collaboration Skills: Waymo values teamwork, so be sure to include examples of how you've successfully collaborated with diverse teams in previous roles. Mention any experience working with large models or in research engineering.
Tailor Your Application: Customize your application materials to reflect the specific requirements and preferences mentioned in the job description. Use keywords from the listing to ensure your application stands out.
How to prepare for a job interview at The Rundown
✨Showcase Your Deep Learning Expertise
Make sure to highlight your experience in applied deep learning during the interview. Be prepared to discuss specific projects where you've successfully implemented state-of-the-art ML techniques and how they contributed to solving complex production problems.
✨Demonstrate Collaboration Skills
Since this role involves working with teams across different locations, emphasize your ability to collaborate effectively. Share examples of past experiences where you worked in a team setting, particularly in research engineering or similar environments.
✨Prepare for Technical Questions
Expect technical questions related to machine learning, data analysis, and simulation. Brush up on your knowledge of large foundation models and be ready to explain how you would design experiments to improve simulation realism.
✨Discuss Metrics for Realism
Be prepared to talk about how you would develop metrics to measure the realism of simulated worlds. This is a key aspect of the role, so having a clear understanding of what makes a simulation realistic will set you apart.
