Frontier Tech Infrastructure Ml Jobs

Join our ML Infrastructure engineering team advancing state-of-the-art ultra-realistic multi-agent simulations using foundation models.

ML training infrastructure that powers our next-generation autonomous transport models.

In this role, you will enable this research effort by building ML tools, infrastructure, managing large datasets, and addressing challenges across the entire end-to-end

Partner cross-functionally with compiler, hardware, firmware, runtime, and infrastructure teams.

The ML Data Infrastructure and Inference Platform team owns the Data as well as the Data infrastructure for all ML Flywheels at Waymo.

Computer Engineering or equivalent practical experience 10+ years on designing/architecting complex, high performance architectures - CPUs, GPUs and/or ML

You'll own real infrastructure from day one, not tickets in a backlog. Interview Process 1.

You will also collaborate with machine learning engineers and data engineers on the ML compute platform and data pipeline infrastructure.

Nice to have: M.Sc or PhD in a ML related area Built an ML optimization framework from scratch before

Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine

An expert in modern ML engineering. You understand the mathematics and systems behind modern ML methods.

Experience in GPU/ML infrastructure or high-performance compute workloads on AWS.

in machine learning pipelines and ML engineers that want to work beyond modeling to join the Data & ML infra group.

engineer, founding ML engineer, or first ML infrastructure hire at a startup You’ve built ML infrastructure in a high-growth or operationally complex

Our current ML stack is primarily Python, PyTorch, CUDA, and distributed GPU training, with custom infrastructure for signal processing, data collection