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

Staff Software Engineer, Simulation ML Infrastructure

London Full-Time 120000 - 170000 £ / 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 is a pioneering autonomous driving technology company focused on safety and innovation.
  • Benefits: Enjoy competitive salary, annual bonuses, equity plans, and generous benefits.
  • Why this job: Join a world-class team to shape the future of autonomous driving and make a real impact.
  • Qualifications: 8+ years in software engineering with strong ML infrastructure experience required.
  • Other info: Work collaboratively across teams and mentor junior engineers in a dynamic environment.

The predicted salary is between 120000 - 170000 £ 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 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 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 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.
  • Experience navigating cross-functional teams and providing technical leadership on 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

Seniority level: Mid-Senior level

Employment type: Full-time

Job function: Engineering and Information Technology

Industries: Technology, Information and Internet

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 London. With a strong focus on innovation and collaboration, employees benefit from a supportive work culture that encourages professional growth through mentorship and access to cutting-edge projects. The company also provides competitive compensation packages, including bonuses and equity incentives, making it an attractive choice for those seeking meaningful and rewarding employment in the tech industry.
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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

Familiarise yourself with the latest advancements in machine learning infrastructure, particularly tools like DeepSpeed and PyTorch. Being able to discuss these technologies confidently during your interview will demonstrate your expertise and passion for the field.

✨Tip Number 2

Network with professionals in the autonomous driving and simulation sectors. Attend relevant meetups or webinars to connect with current employees at Waymo or similar companies, as referrals can significantly boost your chances of landing an interview.

✨Tip Number 3

Prepare to showcase your experience with distributed training techniques and large-scale ML systems. Be ready to discuss specific projects where you successfully implemented these strategies, as this will highlight your practical knowledge and problem-solving skills.

✨Tip Number 4

Stay updated on the latest trends in autonomous driving technology and simulations. Being knowledgeable about current challenges and innovations in the field will allow you to engage in meaningful discussions during interviews, showing that you're not just qualified but also genuinely interested in the industry.

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

Machine Learning Infrastructure Development
Distributed Training Techniques
Large-Scale Model Architectures
DeepSpeed
PyTorch
TensorFlow
Ray
Gradient Sharding
Performance Bottleneck Analysis
Custom Kernels for Compute Efficiency
Autoregressive Transformers
Data Engineering
Architectural Decision-Making
Technical Leadership
Collaboration with Cross-Functional Teams
Mentoring Junior Engineers

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in machine learning infrastructure, particularly with large-scale systems. Emphasise your expertise in tools like DeepSpeed, PyTorch, and TensorFlow, as well as any experience with distributed training techniques.

Craft a Compelling Cover Letter: In your cover letter, express your passion for autonomous driving technology and how your background aligns with Waymo's mission. Mention specific projects or achievements that demonstrate your ability to lead technical initiatives and mentor junior engineers.

Showcase Technical Leadership: Provide examples of how you've successfully navigated cross-functional teams and led projects. Highlight your ability to translate complex technical concepts for diverse audiences, which is crucial for the Staff Software Engineer role.

Highlight Relevant Qualifications: Clearly outline your qualifications, especially the 8+ years of professional software engineering experience and any familiarity with autonomous driving and simulations. This will help you stand out as a strong candidate for the position.

How to prepare for a job interview at Waymo

✨Showcase Your Technical Expertise

Be prepared to discuss your experience with large-scale machine learning systems and the specific tools you've used, such as DeepSpeed or PyTorch. Highlight any projects where you successfully scaled models or optimised infrastructure.

✨Understand the Company’s Mission

Familiarise yourself with Waymo's mission and recent advancements in autonomous driving technology. Being able to articulate how your skills align with their goals will demonstrate your genuine interest in the role.

✨Prepare for System Design Questions

Expect questions that assess your ability to design scalable ML systems. Practice explaining your thought process for architectural decisions and how you would approach managing complex systems in a collaborative environment.

✨Emphasise Collaboration and Leadership

Since the role involves mentoring junior engineers and working across teams, be ready to share examples of how you've led projects or collaborated with cross-functional teams. This will show your ability to foster a positive team culture.

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

    London
    Full-Time
    120000 - 170000 £ / year (est.)
  • W

    Waymo

    1000-5000
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