Jobs Companies NVIDIA Lab Manager - Hardware Engineering

Sobre este puesto de Lab Manager - Hardware Engineering en NVIDIA

NVIDIA · Presencial · India, Bengaluru

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, we are tapping into the unlimited potential of AI to define the next era of computing — an era in which our GPUs act as the brains of computers, robots, and self-driving cars that understand the world. Doing what has never been done before takes vision, innovation, and the world’s best talent.

NVIDIA’s Silicon Co-Design Group is the team that gets every GPU, SoC, and CPU silicon program from first power-on to high-volume production. We are hiring a Lab Manager to own hardware engineering lab operations across our Bangalore, Hyderabad and Pune Design Center.Your labs are where silicon meets reality — where every bring-up, validation experiment, and rework cycle happens, and where a day lost hits the program directly. You own the section: multiple labs, varied product classes, and a team of rework, reflow, and logistics technicians delivering daily for engineering. Your decisions show up in lab uptime, bring-up readiness, capital plan accuracy, and audit outcomes on safety and physical IP. You are the leader the program turns to when a new product class needs a lab spun up fast, when an EHS or security gap surfaces, or when capacity for the next roadmap year hasn’t been planned.

What you will be doing:

  • Own and Run multiple labs across varied product classes — silicon bring-up, validation, and engineering experiments. Lead rework, reflow, and logistics technicians (including outsourced workers); develop them to self-manage opex procurement, planning, and day-to-day execution.

  • Plan ahead of the roadmap. Forecast long-term lab needs — space, power, cooling, thermal, reflow capability, equipment — and own the capital and expense plan that supports it. Drive growth, reconfiguration, and ramp-down as programs evolve.

  • Engage Bring-up early. Partner with Bring-up managers to scope incoming silicon programs — requirements, procurement, budget, staffing — so infrastructure and personnel land ahead of priority milestones, on cost.

  • Hold the safety and security bar. Drive lab EHS compliance and security control. Be the recognized safety champion and physical IP asset expert — set guidelines, run reviews, operate with audit-ready discipline.

  • Run equipment cradle-to-grave. Own capital and expense planning, purchasing, warranty, calibration, and inventory — shipment, import, EC components, bonding — with a clear, auditable process across all labs.

  • Standardize across sites. Coordinate with global lab managers to learn and propagate best practices and standardize lab operations where it adds leverage.

  • Role may involve travel across our Bangalore, Hyderabad, and Pune Design Centers

What we need to see:

  • Bachelor’s degree in Electrical Engineering or a related field (or equivalent experience), with overall 8+ years of experience in silicon/HW lab setup, management, and maintenance.

  • At least 3+ years managing a technical lab environment and leading teams across sites, with a track record of owning a multi-lab section — including capital and expense equipment planning, vendor and outsourced-worker management, and inventory/logistics tracking.

  • Hands-on experience operating lab equipment (oscilloscope, DAQ, and other common equipment) and consumer hardware assembly/teardown, solder/rework — with familiarity in HW bring-ups, computer systems, and debugging.

  • Experience working with multi-functional teams — SW, validation, ASIC, and other hardware/software functions — with excellent communication abilities across sites.

Ways to stand out from the crowd:

  • Experience with CPU/SOC chip bring-up and validation process.

  • Multi-site or global lab coordination experience — shared standards, vendor frameworks, or capacity planning across regions.

  • Comfortable using AI productivity tools (Claude, Copilot, or equivalent) to compress reporting, analysis, and operational workflows — with judgment about where AI helps and where it doesn’t.

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