Jobverse.io
Staff Machine Learning Infrastructure Engineer, Simulation
Get notified of more jobs like this · No spam, ever
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Waymo
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. They are seeking an experienced Senior Machine Learning Infrastructure Engineer to lead the development of advanced AI/ML infrastructure for simulations that support the Waymo Driver. The role involves collaborating with various teams to improve simulation realism and mentoring junior engineers.
Get help with your application
Your very own career expert that helps elevate your application to the next level.
Responsibilities
- Be part of a world-class, high-performing research engineering team to advance the state of the art of ultra realistic multi-agent simulations using foundation models
- Collaborate closely with the core Google DeepMind and Waymo Realism Modeling teams in London, and Waymo Oxford to use the large 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 deployment, and provide guidance on architectural decisions and technical directions. Own large, complex systems, driving architectures that meet technical and business objectives
- Design and scale large distributed systems covering the ML lifecycle, supporting planet-scale dataset generation and model training
- Collaborate cross-functionally to derive performance and system-level requirements for large ML systems. Translate product/business goals into measurable technical deliverables, ensuring system component alignment
- Mentor junior engineers, growing their expertise and fostering a collaborative culture
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location