Manager, System Software Engineering - Factory

NVIDIA•Santa Clara, CA

7d•$224,000 - $356,500•Onsite

About The Position

NVIDIA is seeking a highly motivated and creative Engineering Manager to lead the Factory System Software and Diagnostics Integration end-to-end. This role involves building and leading a global engineering team responsible for delivering embedded code, application programs, and diagnostic updates that support factories building NVIDIA's GPU- and DPU-based products. The work includes supporting tightly coupled rack-scale systems like GB200/GB300 NVL72 and next-generation platforms, covering both concurrent NPI ramps and sustaining production. The manager will collaborate with system architects, firmware developers, SWQA, product engineering, compliance and security teams, program and product management, and ODM/CM manufacturing partners to ensure high-quality releases reach factory floors without issues being discovered there first.

Requirements

10+ overall years in the software industry with specialization in system software and/or firmware development.
3+ years of engineering management or technical leadership experience, including building and leading geographically distributed teams.
BS, MS, or PhD in CS, CE, EE, or a related technical field — or equivalent experience.
Proven track record of shipping scalable server products through factory ramps — from NPI bring-up to mass production — collaborating with hardware, firmware, manufacturing, diagnostics, and QA teams.
Experience working with ODM/OEM partners to deliver quality servers and solutions for large-scale data centers.
A self-starter who loves finding creative solutions to complicated problems, with excellent written and oral communication skills — including executive-level reporting — strong work ethic, and dedication to teamwork.
Flexibility to work and communicate effectively across teams, partners, and time zones.

Nice To Haves

Experience leading bring-up for sophisticated rack-scale compute architectures like GB200/GB300 NVL72.
Familiarity with manufacturing test flows (L6/L10/L11/L12 stations), factory test coverage, and MES integration.
Hands-on experience with x86/ARM system architecture and coding (C/C++, Python).
Experience with SCM (Git, Perforce) and project management tools (Jira).
Track record of integrating AI/LLM tooling into engineering workflows — for triage, validation, log analysis, or test generation.
Experience standing up follow-the-sun support organizations with measurable response SLAs.

Responsibilities

Build, lead, mentor, and grow a global factory engineering team spanning the US and Taiwan, operating a follow-the-sun coverage model with on-site presence at ODM/CM partner factories.
Own hiring, career development, calibration, and succession planning.
Define Factory readiness scope and workflows for rack scale products, coordinating multi-functionally with product management, technical architects, and program management.
Deliver those workflows through the validation matrix, ensuring delivered firmware and software is of the highest quality and that solutions scale and are resilient.
Own technical leadership for how firmware, software, and diagnostics releases reach factories building rack-scale systems, including tightly coupled compute and switch trays.
Build the end-to-end infrastructure and workflows that ensure every release arrives with efficient quality.
Left-shift release quality by partnering with developers, SWQA, and product engineering in a fast-moving environment with end-to-end CI/CD.
Enforce well-placed quality gates at every product landmark, publish and track indicators at a regular cadence, and report release progress to collaborators and executives.
Own the factory escalation path, including triage SLAs, 24x7 coverage, failure root-cause and deflection, and bonepile burn-down to minimize line-down time during NPI ramps and mass production.
Shape the team's roadmap and drive innovation with a strong focus on automation and AI-assisted validation and triage.
Continuously analyze factory processes, systems, and workflows to identify improvement and optimization opportunities, remove bottlenecks, document and publish standard operating procedures (SOPs), and ensure the team performs efficiently and transparently against measurable targets.