Level

NVIDIA

Senior System Performance Engineer

NVIDIA is hiring a Senior System Performance Engineer in Bengaluru, India. Level rates it ; you can apply on Level.

AI in this role

Lead silicon performance validation and apply data-driven machine learning methods to analyze telemetry data and optimize power controllers.

python
silicon-validationpower-optimizationperformance-tuningmachine-learningdata-analysis

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a "learning machine" that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life's work to amplify human imagination and intelligence. Make the choice to join us today!

 

As part of the Silicon Solutions Team, we architect and deliver groundbreaking solutions for productizing NVIDIA's chips into consumer, professional, server, mobile, and automotive markets. Silicon characterization, correlation to arch & design expectations, finalize product specifications, develop productization techniques and infrastructure around it are part of our responsibilities. Dealing with challenges of the latest process node technologies is also part of the work. Join this dynamic team as a Senior System Perf Engineer, and help craft the future of computing in Bengaluru.


What you'll be doing:

  • Lead the productization of Performance controllers from pre-silicon planning through bring-up, tuning, validation, and production.
  • Collaborate with architecture, design, firmware, and software teams to define controller requirements & features , identify improvements and translate new capabilities into production-ready solutions.
  • Characterize and tune controller behaviour across workloads, operating conditions, silicon variation, and product power and thermal limits. Maximize the perf and Perf/Watt with-in architectural bottlenecks & limitations, Power/Thermal system limits to provide best customer experience for the products
  • Correlate silicon behaviour with pre-silicon expectations, debug & resolve complex problems during bring up and final closed loop performance stage involving silicon HW, firmware, software, power delivery network, system thermals etc.
  • Apply AI/ML and data-driven methods to analyze silicon characterization and HW telemetry data, identify anomalies and trends, accelerate controller tuning and improve debug as well as silicon validation execution efficiency.

 

What we need to See:

  • B. Tech or M. Tech in Electronics Engineering stream.
  • At least 5+ years of proven experience in silicon validation, system level design, and power/performance optimization.
  • Strong understanding of aspects related to silicon power and performance, technology node impacts, Hardware and Software interactions at system level.
  • Hands-on experience with silicon bring up, validation and productization
  • Good HW architectural understanding and orientation
  • Very good problem solving and hardware debugging skills.
  • Strong good data analysis and logical reasoning skills.
  • Strong familiarity with HW lab environment.
  • Must be a great teammate and ready to collaborate with global teams from diverse cultural backgrounds in a high energy environment.

Ways to stand out from the crowd:

  • Extensive background in DVFS, voltage/frequency management, HW telemetries, Performance throttling, silicon protection mechanisms on advanced ASIC/SoC products.
  • Contributions that improved controller behaviour, silicon performance, power efficiency, thermal management, bring-up/productization methodologies.
  • Experience connecting controller behaviour across simulation, silicon, firmware, and system-level measurements and converting findings into production tuning.
  • Experience applying AI/ML to engineering workflows, such as controller tuning, characterization analytics, anomaly detection, or debug assistants deployed beyond personal use.

With every new architecture and process node, balancing performance against power and thermal limits becomes tougher. Our controllers are at the forefront of this issue: drawing out the performance the silicon was crafted to achieve while shielding it when workloads push its limits. If you like understanding dynamic silicon behaviour, addressing hardware-software challenges, and influencing NVIDIA products at scale, we'd love to connect!

 

#LI-Hybrid

How we rate this

Senior System Performance Engineer at NVIDIA rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Silicon ValidationPower OptimizationPerformance TuningMachine learningData AnalysisPython

Questions you could be asked

  1. Tell me about a project where silicon validation was part of your work. What did you do?
  2. Tell me about a project where power optimization was part of your work. What did you do?
  3. Tell me about a project where performance tuning was part of your work. What did you do?
  4. Tell me about a project where machine learning was part of your work. What did you do?
  5. Tell me about a project where data analysis was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Silicon Validation, Power Optimization, Performance Tuning, Machine learning, and Data Analysis. 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.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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