Head of AI Infrastructure Platform

NVIDIA Corporation; Westford (MA); On-site; USD 224,000 - 431,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA Corporation in Massachusetts is seeking an Engineering Manager to lead one of our AI infrastructure teams. You will hire, mentor, and grow engineers, own platform end-to-end, and collaborate with research teams to translate model training requirements into scalable solutions.

The role emphasizes reliability, scalability, and performance across large GPU clusters and Kubernetes-based platforms. You will shape the platform, set ownership, drive automation, and contribute to open-source

Qualifications

• BS or MS in Computer Science, Computer Engineering or related field, or equivalent experience.
• 12+ years in software engineering, with 5+ years managing engineering teams.
• Track record of building large-scale distributed systems in production.

Responsibilities

• Lead, hire and grow a team of software and systems engineers, including senior and staff-level engineers and tech leads.
• Own a core part of the AI infrastructure platform end to end: roadmap, architecture, reliability and on-call health.
• Turn research needs into platform capabilities by working directly with model training teams.
• Set clear ownership and decision rights for your area with documented decisions and clean interfaces.
• Drive engineering quality at fleet scale with automation, observability, and safe rollouts across clusters.
• Partner with infrastructure, storage, networking, Kubernetes and cloud-provider teams across NVIDIA and with external vendors and open-source communities.
• Measure reliability and latency to set priorities for researchers.
• Contribute to the shared Kubernetes-based platform codebase and open-source path.

Skills

Engineering management

Distributed systems

Kubernetes

Communication

Leadership

Education

BS/MS in CS or related field

Job description

NVIDIA Corporation in Massachusetts is seeking an Engineering Manager to lead one of our AI infrastructure teams. You will hire, mentor, and grow engineers, own platform end-to-end, and collaborate with research teams to translate model training requirements into scalable solutions.

The role emphasizes reliability, scalability, and performance across large GPU clusters and Kubernetes-based platforms. You will shape the platform, set ownership, drive automation, and contribute to open-source