Senior Inference Engineer, GPU Kernel Optimization

Posted 3 Days Ago
Be an Early Applicant
4 Locations
In-Office
184K-288K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Develop silicon-accurate GPU kernel microbenchmarks, model-level performance analysis, and agentic kernel optimization to maximize LLM inference throughput and latency. Attribute bottlenecks across kernel, compiler, and runtime, produce optimization policies, and collaborate with compiler, hardware, kernel, and framework teams to deliver production-grade performance improvements.
Summary Generated by Built In

We're now looking for a Sr. Inference Engineer, for GPU Kernel Optimization! What does it take to push every LLM inference operation to its performance ceiling? Our LLM Inference Performance Analysis and Optimization team builds the answer from the ground up. We develop silicon-measured kernel benchmarking infrastructure, model-level performance projection tooling, and agentic optimization systems that improve GPU kernels at the assembly layer. Our team works closely with compiler, kernel, hardware, and framework organizations across NVIDIA to surface bottlenecks and ship measurable gains. If driving GPU performance at the frontier of LLM inference sounds like your kind of challenge, we'd love to meet you!

What you'll be doing:

The role drives three interconnected systems, all aimed at accelerating NVIDIA's LLM inference stack. The first is GPU kernel microbenchmarking: measuring competing kernel implementations at real-silicon fidelity across the full configuration space that production LLM deployments demand. The second is end-to-end model performance analysis: connecting performance evidence to model-level serving economics, surfacing high-value optimization opportunities, and producing optimization policies for production inference deployments. The third is agentic kernel optimization: applying AI-driven analysis to diagnose performance gaps, explore optimization opportunities across the kernel ecosystem, and validate findings with rigorous silicon measurements. All three streams converge in close collaboration with compiler, hardware, kernel, and framework teams to deliver upstream improvements and production-grade performance gains.

What we need to see

  • Master's or PhD in Computer Science, Computer Engineering, or a related field, or equivalent experience.

  • 6+ years of relevant industry experience.

  • Experience building or directing agentic AI systems — code generation, automated optimization, or multi-step reasoning workflows.

  • Strong Python and C++ skills with proven software engineering fundamentals.

  • Hands-on GPU profiling with CUPTI, NSYS, and NCU; proven track record to attribute bottlenecks across kernel execution, compiler decisions, and runtime scheduling.

  • Direct experience with LLM inference frameworks such as TRT-LLM, SGLang, or vLLM and clear understanding of how kernel selection drives model-level throughput and latency.

  • Working knowledge of GPU kernel optimization — CUDA, CUTLASS, Triton, or equivalent — and the ability to read PTX or SASS output.

Ways to stand out from the crowd

  • Deep knowledge of SASS/PTX-level kernel analysis, compiler middle-end optimization, or GPU code generation pipelines (LLVM, MLIR, ptxas, or similar).

  • Track record shipping agentic systems end-to-end — tool invent, multi-agent orchestration, and silicon-verified validation — within a performance engineering or kernel optimization context.

  • Active contributions to open-source LLM inference or GPU kernel libraries (FlashInfer, Triton, CUTLASS, or similar).

Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ 

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 31, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Skills Required

  • Master's or PhD in Computer Science, Computer Engineering, or related field, or equivalent experience.
  • 6+ years of relevant industry experience.
  • Experience building or directing agentic AI systems (code generation, automated optimization, multi-step reasoning workflows).
  • Strong Python skills.
  • Strong C++ skills.
  • Hands-on GPU profiling experience with CUPTI, NSYS, and NCU.
  • Direct experience with LLM inference frameworks such as TRT-LLM, SGLang, or vLLM.
  • Working knowledge of GPU kernel optimization (CUDA, CUTLASS, Triton, or equivalent) and ability to read PTX or SASS output.

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

NVIDIA Insights

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s 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 — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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