Staff Software Engineer, Simulation ML Infrastructure
Staff Software Engineer, Simulation ML Infrastructure

Staff Software Engineer, Simulation ML Infrastructure

City of London Full-Time 150000 - 162000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Lead the development of advanced AI/ML infrastructure for realistic simulations.
  • Company: Waymo, a pioneering autonomous driving technology company.
  • Benefits: Competitive salary, bonus program, equity incentives, and generous benefits.
  • Why this job: Join a world-class team and shape the future of autonomous driving.
  • Qualifications: 8+ years in software engineering with a focus on machine learning infrastructure.
  • Other info: Mentor junior engineers and thrive in a collaborative environment.

The predicted salary is between 150000 - 162000 £ 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 Simulation Machine Learning Infrastructure team builds scalable AI/ML infrastructure to accelerate the Simulator team in sustainably innovating and building state-of-the-art simulations of realistic environments for the testing and training of the Waymo Driver. To increase the fidelity and steerability of the simulations, we employ large foundation models trained on massive datasets to model the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists), roads, traffic control systems, and weather

We are looking for an experienced Staff Machine Learning Infrastructure Engineer to lead the development of advanced AI/ML infrastructure for multi-billion parameter foundation models in ML accelerator-friendly simulations. Your expertise in massive model scaling, ML accelerators, and distributed training will be required for designing and scaling our systems.

This role reports to an Engineering Manager.

In this role, you’ll:

  • Be part of a world-class, research engineering team to improve the of ultra realistic multi-agent simulations using foundation models.
  • Collaborate with the core Waymo Realism Modeling team in London and Waymo Oxford to use large foundation models to improve sim realism.
  • Provide deep technical leadership on large-scale ML model architectures, especially for autonomous vehicle models. Work at the intersection of data engineering, model development, and simulations, and provide guidance on architectural decisions and technical directions. Manage complex systems, driving architectures that meet technical and goals.
  • Design and scale large distributed systems covering the ML lifecycle, supporting planet-scale dataset generation, model training, and evaluation.
  • Collaborate to derive performance and system-level requirements for large ML systems. Translate product/business goals into measurable technical deliverables, ensuring system component agreement.
  • Mentor junior engineers, growing their expertise and promoting a collaborative culture.

Preferred qualifications

  • 8+ years of professional software engineering experience, with at least 5 years in machine learning infrastructure such as developing, scaling, training, deploying, and optimizing large-scale machine learning systems from data to model.
  • Solid experience in the development and optimization of machine learning infrastructure tools like DeepSpeed, PyTorch, TensorFlow, Ray, or similar frameworks.
  • Expertise in distributed training techniques, including gradient sharding and optimization strategies for scaling large models across ML accelerator profiling tools to uncover performance bottlenecks. Familiarity with custom kernels for compute based efficiency.
  • Experience with state-of-the-art machine learning models such as autoregressive transformers.
  • With experience navigating cross-functional teams and providing technical leadership projects across multiple organizations.
  • with the ability to translate complex technical concepts for a broad audience.
  • Practical familiarity in Autonomous Driving, Simulations, and ML accelerators is a plus.

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 £150,000 — £162,000 GBP

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Staff Software Engineer, Simulation ML Infrastructure employer: Waymo

Waymo is an exceptional employer, offering a unique opportunity to work at the forefront of autonomous driving technology in a collaborative and innovative environment. With a strong focus on employee growth, Waymo provides extensive mentorship opportunities and encourages continuous learning, ensuring that team members can thrive in their careers while contributing to meaningful advancements in mobility. Located in London, employees benefit from a vibrant tech community and access to cutting-edge resources, making it an ideal place for those passionate about AI and machine learning.
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Contact Detail:

Waymo Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Staff Software Engineer, Simulation ML Infrastructure

✨Tip Number 1

Network like a pro! Reach out to folks in the industry, especially those at Waymo. Use LinkedIn to connect and engage with them. A friendly chat can sometimes lead to opportunities that aren’t even advertised!

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your projects related to machine learning infrastructure. Whether it’s GitHub repos or personal blogs, let your work speak for itself. We love seeing what you can do!

✨Tip Number 3

Prepare for technical interviews by brushing up on your knowledge of distributed training techniques and ML frameworks. Practice coding challenges and system design questions. We want to see how you think and solve problems!

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at Waymo. Let’s make it happen!

We think you need these skills to ace Staff Software Engineer, Simulation ML Infrastructure

Machine Learning Infrastructure
Distributed Training Techniques
Large-Scale ML Model Architectures
DeepSpeed
PyTorch
TensorFlow
Ray
Gradient Sharding
Performance Bottleneck Profiling
Custom Kernels
Autoregressive Transformers
Data Engineering
Technical Leadership
Collaboration with Cross-Functional Teams
Mentoring Junior Engineers

Some tips for your application 🫡

Tailor Your CV: Make sure your CV is tailored to the role of Staff Software Engineer. Highlight your experience with ML infrastructure and any relevant projects that showcase your skills in large-scale model architectures.

Craft a Compelling Cover Letter: Your cover letter should tell us why you're passionate about autonomous driving and how your background aligns with our mission. Share specific examples of your work that relate to the job description.

Showcase Your Technical Skills: Don’t just list your skills; demonstrate them! Include details about the tools and frameworks you've used, like PyTorch or TensorFlow, and any significant achievements in scaling ML systems.

Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you’re considered for the role!

How to prepare for a job interview at Waymo

✨Know Your Stuff

Make sure you brush up on your knowledge of machine learning infrastructure, especially tools like DeepSpeed, PyTorch, and TensorFlow. Be ready to discuss your experience with large-scale ML systems and how you've tackled challenges in scaling and optimising them.

✨Showcase Your Leadership Skills

Since this role involves mentoring junior engineers and providing technical leadership, prepare examples of how you've led projects or teams in the past. Highlight your ability to translate complex concepts for a broad audience—this will show that you can communicate effectively across different teams.

✨Understand the Company’s Mission

Familiarise yourself with Waymo's mission and the specifics of their technology. Being able to articulate how your skills align with their goals, especially in improving autonomous driving simulations, will demonstrate your genuine interest in the role and the company.

✨Prepare for Technical Questions

Expect in-depth technical questions related to distributed training techniques and performance optimisation strategies. Practice explaining your thought process and problem-solving approach, as this will help you stand out as a candidate who can think critically under pressure.

Staff Software Engineer, Simulation ML Infrastructure
Waymo
Location: City of London
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  • Staff Software Engineer, Simulation ML Infrastructure

    City of London
    Full-Time
    150000 - 162000 £ / year (est.)
  • W

    Waymo

    1000-5000
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