Waymo
Technology
SeniorMachineLearningInfrastructureEngineer,Simulation
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Machine Learning Infrastructure Engineer, Simulation at Waymo. Skills: Machine Learning Infrastructure, Foundation Models, Distributed Systems, ML Accelerators. Lead ML infrastructure development. Design advanced AI/ML infrastructure”
Industry & Context.
Uncover performance bottlenecks
What They're Looking For.
Must Have
BS in Computer Science or equivalent, 5+ years software engineering, 3+ years ML infrastructure
Nice to Have
10+ years software engineering, 5+ years ML infrastructure, DeepSpeed experience, PyTorch experience, TensorFlow experience, Gradient sharding expertise, ML accelerator profiling tools, Auto-regressive transformers knowledge, Custom kernels familiarity, Autonomous Driving familiarity, Simulations familiarity, ML accelerators familiarity
What You'll Do.
Lead ML infrastructure development
Design advanced AI/ML infrastructure
Scale AI/ML infrastructure
Develop foundation models
Train foundation models
Collaborate with research teams
Provide technical leadership
Guide architectural decisions
Drive system architectures
Scale distributed systems
Generate planet-scale datasets
Train large ML systems
Derive system requirements
Align system components
Mentor junior engineers
How You'll Work.
Team & Collaboration
Research engineering team; Google DeepMind teams; Waymo Realism Modeling; Waymo Oxford teams; Cross-functional teams
Communication Scope
Translate technical concepts
Process & Methodology
Technical deliverables
Full Job Description
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 ML 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 but not limited to, realistic agents (vehicles, pedestrians, cyclists, motorcyclists etc.), roads, traffic control systems, and weather etc. We seek an experienced Senior 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. You will: 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 dee
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