NVIDIA

NVIDIA

Posted via Workday

Senior Software Engineer, Matrix Multiplication

Posted Aug 5, 2026

Role at a glance

Salary
$184K – $287.5K/yr
Location
10 Locations, California, United States
Work arrangement
On-site
Employment
Full-time
Experience
6+ years (academic/ industry) experience with ML/DL systems development preferable
Education
Masters degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); PhD are preferred

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Role Summary

AI-generated

The AI systems engineering team develops software for efficient AI inference on NVIDIA hardware. The role focuses on libraries, code generators, GPU kernels, abstractions, runtimes, and compilers that accelerate large language models, agents, and other AI workloads, with collaboration across deep learning frameworks, libraries, kernels, and GPU architecture teams.

What You'll Do

  • Innovate and develop new AI systems technologies for efficient inference
  • Design, implement, and optimize kernels for high-impact AI workloads
  • Design and implement extensible abstractions for LLM serving engines
  • Build efficient just-in-time domain-specific compilers and runtimes
  • Collaborate with engineers across deep learning frameworks, libraries, kernels, and GPU architecture teams
  • Contribute to open source communities such as FlashInfer, vLLM, and SGLang

Generated from the employer's posting. Verify important details before applying.

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Qualifications

Master's degree in Computer Science, Electrical Engineering, or related field, or equivalent experience; 6+ years of academic or industry experience with ML/DL systems development; strong deep learning framework experience; strong Python and C/C++ skills; strong GPU kernel development and performance optimization experience, including hands-on Matrix Multiplication.

Required

  • Master's degree in Computer Science, Electrical Engineering, or related field, or equivalent experience
  • 6+ years (academic/ industry) experience with ML/DL systems development preferable
  • Strong experience in developing or using deep learning frameworks such as PyTorch, JAX, TensorFlow, or ONNX
  • Strong Python and C/C++ programming skills
  • Strong experience in GPU kernel development and performance optimizations using CUDA C/C++, cuTile, Triton, or similar
  • Hands-on experience with Matrix Multiplication

Preferred

  • PhD
  • Background in domain specific compiler and library solutions for LLM inference and training, such as FlashInfer or Flash Attention
  • Expertise in inference engines like vLLM and SGLang
  • Expertise in machine learning compilers such as Apache TVM or MLIR
  • Open source project ownership or contributions

Original job description

Content provided by the employer

We're looking for outstanding AI systems engineers to develop groundbreaking technologies in the inference systems software stack! We build innovative AI systems software to accelerate for AI inference. As a member of the team, you'll develop libraries, code generators, and GPU kernel technologies for NVIDIA's hardware architecture. This means designing and building things like new abstractions, efficient attention kernel implementations, new LLM inference runtimes components, and kernel code generators to accelerate large language models, agents, and other high-impact AI workloads.

What you'll be doing:

  • Innovating and developing new AI systems technologies for efficient inference

  • Designing, implementing, and optimizing kernels for high impact AI workloads

  • Designing and implementing extensible abstractions for LLM serving engines

  • Building efficient just-in-time domain specific compilers and runtimes

  • Collaborating closely with other engineers at NVIDIA across deep learning frameworks, libraries, kernels, and GPU arch teams

  • Contributing to open source communities like FlashInfer, vLLM, and SGLang

What we need to see:

  • Masters degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); PhD are preferred

  • 6+ years (academic/ industry) experience with ML/DL systems development preferable

  • Strong experience in developing or using deep learning frameworks (e.g. PyTorch, JAX, TensorFlow, ONNX, etc) and ideally inference engines and runtimes such as vLLM, SGLang, and MLC.

  • Strong Python and C/C++ programming skills

  • Strong experience in GPU kernel development and performance optimizations (especially using CUDA C/C++, cuTile, Triton, or similar) with hands-on experience with Matrix Multiplication

Ways to stand out from the crowd:

  • Background in domain specific compiler and library solutions for LLM inference and training (e.g. FlashInfer, Flash Attention)

  • Expertise in inference engines like vLLM and SGLang

  • Expertise in machine learning compilers (e.g. Apache TVM, MLIR)

  • Open source project ownership or contributions

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 August 14, 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.

NVIDIA

About the company

NVIDIA

Large Enterprise

NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.