NVIDIA Logo

NVIDIA

Deep Learning Compiler Engineer

Posted 28 Days Ago
Be an Early Applicant
In-Office or Remote
4 Locations
152K-242K Annually
Mid level
In-Office or Remote
4 Locations
152K-242K Annually
Mid level
Design and implement CUDA Tile compiler transformations, MLIR dialects, lowering passes, and optimization techniques for NVIDIA GPUs. Optimize tile-based kernel performance across GPU generations, define public APIs, conduct performance analysis, and develop robust software, tests, and debugging workflows. The role requires independent project ownership and collaboration within a product-focused engineering team.
The summary above was generated by AI

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

We are hiring software engineers for the Tensor IR & CUDA Tile team. NVIDIA GPUs are at the center of the deep learning revolution and continue to enable breakthroughs in generative AI, large language models, recommendation systems, speech recognition, image classification and other areas. Come join us to work with a top-notch team and have broad impact across the entire deep learning community.

What you'll be doing:

In this role, you will work on CUDA Tile and TensorIR compiler technologies for NVIDIA GPUs. CUDA Tile is a new tile-based programming model that shipped with CUDA 13.1, and TensorIR is an open-source compiler infrastructure project that uses CUDA Tile to generate high-performance GPU kernels. You will design and implement compiler transformations, develop MLIR-based dialects and lowering passes, and optimize the performance of tile-based kernels to ensure they execute efficiently across multiple generations of NVIDIA GPU architectures. The scope of these efforts includes defining public APIs, crafting and implementing compiler and optimization techniques, performance optimization, and other general software engineering work.

What we need to see:

  • Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering or a related field (or equivalent experience)

  • 3+ years of relevant work or research experience in compiler optimization, performance analysis and IR design.

  • Ability to work independently, define project goals and scope, and lead your own development effort.

  • Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design.

  • Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team.

Ways to stand out from the crowd:

  • Knowledge of CPU and/or GPU architecture. CUDA or OpenCL programming experience.

  • Experience with the following technologies: MLIR, LLVM, XLA, TVM and deep learning models and algorithms.

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 27, 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.

#deeplearning
HQ

NVIDIA Santa Clara, California, USA Office

2701 San Tomas Expressway, Santa Clara, CA, United States, Santa Clara

NVIDIA San Francisco, California, USA Office

San Francisco, United States

NVIDIA San Jose, California, USA Office

San Jose, United States

Similar Jobs

57 Minutes Ago
Remote
US
141K-229K Annually
Senior level
141K-229K Annually
Senior level
Consumer Web • eCommerce • Machine Learning • Software • Sports • Analytics
Leads product strategy, roadmap, and continuous improvement for PSA Vault and warehouse management systems. Oversees operational workflows including receiving, storage, inventory, fulfillment, and shipping while improving integrations with grading, marketplace, and logistics systems. Partners with Engineering, Operations, and business stakeholders to define requirements, prioritize initiatives, measure outcomes, and enhance customer experiences. The role also identifies AI and automation opportunities and coordinates cross-functional delivery across the Collectors ecosystem.
Top Skills: AIAutomationEbayProshipWarehouse Management Systems (Wms)
An Hour Ago
Easy Apply
Remote or Hybrid
United States
Easy Apply
98K-193K Annually
Senior level
98K-193K Annually
Senior level
Big Data • Cloud • Software • Database
Serve as the strategic compensation partner for Sales, advising senior leaders on offers, equity, leveling, promotions, retention, benchmarking, and compensation cycles. Analyze market and internal data, support incentive-plan governance and modeling, lead competitive intelligence, improve compensation programs, manage strategic projects, and develop manager enablement materials. Partner closely with Finance, Sales Operations, Recruiting, Legal, and HR while presenting recommendations to executive stakeholders.
Top Skills: RadfordWtw
An Hour Ago
Remote or Hybrid
United States
17-25 Hourly
Junior
17-25 Hourly
Junior
Artificial Intelligence • Automotive • Greentech • Information Technology • Machine Learning • Software • Cybersecurity
Provides technical customer support for Dealertrack Dealer Management Software. Troubleshoots client issues, analyzes dealership transaction documents, configures and codes forms, adds data bindings, resolves validation and calculation errors, documents cases, manages escalations, and maintains client relationships. The role requires phone-based support, analytical problem-solving, attention to detail, schedule flexibility, and proficiency with Microsoft Office. Knowledge of JavaScript and Dealertrack DMS is preferred.
Top Skills: Dealertrack DmsJavaScriptExcelMicrosoft OutlookMicrosoft WordPdf

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account