Engineering Manager

Machine Learning Manager – Platform & Infrastructure

Location: Sunnyvale, CA (Onsite)

Compensation: $350,000 base (DOE) Bonus & Equity

A leading company and industry powerhouse leading the future of physical AI and valued at $15B dollars. They're creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Already servicing automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infra, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the national governing bodies and their allies, trust the company’s solutions to deliver TRUE physical intelligence. Headquartered in California, they've 10 offices worldwide.

Opportunity :

As an ML Manager on the Platform & Infra team, you'll lead a world-class group of engineers focused on building the infrastructure that powers Physical AI at scale. Your team will own three critical areas: Training & Inference Orchestration, where we build frameworks to efficiently schedule and run massive jobs across thousands of GPUs; GPU Cluster Architecture, where we design and scale what will be the largest GPU cluster for Physical AI in the industry; and Performance Optimization, where we push the limits of hardware utilization, throughput, and cost efficiency for large-scale training and inference workloads.

You'll work at the intersection of systems engineering and ML, partnering directly with stack development and research teams to remove bottlenecks and accelerate the path from experimentation to production.

Requirements:

• 3 years of engineering management experience, ideally leading ML infrastructure or platform teams
• Deep experience with distributed systems, GPU computing, or large-scale ML infrastructure
• Direct experience building or operating large GPU clusters (1,000 GPUs)
• Strong understanding of distributed training frameworks

Nice to have:

• Background in training optimization techniques
• Experience with inference optimization
• Familiarity with Physical AI domains such as autonomous driving, robotics, or simulation

Get in touch for more information or apply today for immediate consideration!