Senior Silicon Product Definition Engineer
NVIDIA is hiring a Senior Silicon Product Definition Engineer in Bengaluru, India. Level rates it ; you can apply on NVIDIA.
Level's read on this job
- Little AI ●○○○ is how Level rates this role: aI is not part of the work.
- Tools and skills the posting cites include ChatGPT, Claude and Copilot.
- Level classifies it as a senior role.
- Level lists 2,700+ other open roles at NVIDIA.
AI in this role
Senior Silicon Product Definition Engineer at NVIDIA responsible for optimizing GPU, SoC, and CPU performance using statistical models and automation.
NVIDIA has transformed computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, we're defining the next era of computing, where GPUs power the computers, robots, and autonomous vehicles that understand the world. NVIDIA's Silicon Co-Design Group (SCG) gets every GPU, SoC, and CPU program from first power-on to high-volume production. We sit at the crossroads of architecture, design, marketing, operations, and productization, serving Datacenter, Server, Gaming, Robotics, Automotive, and Embedded markets.
We are hiring a Senior Silicon Product Definition Engineer to turn complex silicon and system data into decisions that maximize performance, power efficiency, yield, and quality. You will define product configurations, identify limiting constraints, and drive optimization from early bring-up through production. This is not a pure data-analysis or validation-only role—you will connect silicon behavior, platform requirements, market needs, and manufacturing realities to determine how products are productized. The exceptional hire uses AI deliberately to compress analysis and debug cycles.
What you'll be doing:
Own product-definition analysis across performance, power, yield, and quality, using large silicon datasets to identify product opportunities, risks, and trade-offs.
Drive product-specific configurations by isolating frequency- power and thermal-limiting constraints and translating findings into silicon, firmware, BIOS, driver, and platform changes.
Build statistical models, automation, and visualization workflows that improve decision quality.
Partner with Tools and Methodology teams to left-shift data modeling, test procedures, and closed-loop analysis infrastructure from post-silicon learning into future programs.
Lead multi-functional root-cause closure with architecture, design, validation, software/firmware, applications engineering, manufacturing, and operations teams from bring-up through production.
Evaluate performance-per-watt, process-voltage-temperature behavior, yield, and quality trade-offs, and drive productized fixes through implementation and confirmation.
Translate complex silicon and system signals into crisp, decision-ready options that give executive leadership clarity on product configuration, performance targets, and program-impacting risks.
Own and deliver BIOS-level VF settings across thermal, power, and frequency domains — debugging issues and driving fixes through cross functional teams to close on Power, Thermal, Performance, Yield and Quality gaps.
What we need to see:
BS or MS in Electrical Engineering, Electronics Engineering, Systems Engineering.
5+ years of experience in silicon product definition, post-silicon characterization, product engineering, or performance and power analysis for GPU, CPU, SoC, or other complex silicon products.
Hands-on experience with silicon bring-up, performance-per-watt analysis, optimization across process, voltage, and temperature conditions.
Strong programming and data-analysis skills using Python and one or more of Perl, JMP, SQL, or equivalent tools, with practical knowledge of statistics and large-dataset manipulation.
Strong technical foundation in digital design, circuit analysis, computer architecture, critical-path analysis, process technology, and transistor/device physics.
Working knowledge of the system stack, including firmware, BIOS, drivers, operating-system behavior, and software applications that influence silicon performance and power.
Demonstrated ability to drive ambiguous technical issues to root-cause closure across globally distributed, multi-functional teams.
Strong written and verbal communication; able to translate complex technical issues into crisp, decision-ready options for executive leadership.
Ways to stand out from the crowd:
Track record of defining and shipping product configurations that measurably improved performance, power efficiency, yield, quality, or time to market.
Experience with advanced process nodes and high-complexity GPU, CPU, AI accelerator, automotive, or datacenter products.
Experience building reusable product-definition methodologies, statistical models, or automation adopted across multiple silicon programs.
Proficiency with AI productivity tools such as Claude, Copilot, ChatGPT, or equivalent to accelerate analysis, debug, drafting, and decision-making workflows—with clear outcomes and appropriate guardrails.
Comfort navigating ambiguity, building technical structure in speed-of-light silicon programs, and collaborating with global teams from diverse cultural backgrounds.
With competitive salaries and a generous benefits package, NVIDIA is widely considered one of the world's most desirable technology employers. We welcome you to join our team and help define the next era of accelerated computing.
#LI-Hybrid
How we rate this
Senior Silicon Product Definition Engineer at NVIDIA rates 20 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where silicon design was part of your work. What did you do?
- Tell me about a project where performance analysis was part of your work. What did you do?
- Tell me about a project where statistical modeling was part of your work. What did you do?
- Tell me about a project where automation was part of your work. What did you do?
- Walk me through how you've used ChatGPT in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Silicon Design, Performance Analysis, Statistical Modeling, Automation, and ChatGPT. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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