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Mlir Jobs (NOW HIRING)

Senior Software Engineer, CUTLASS Platform

Redmond, WA · On-site

$137K - $180K/yr

Contribute to the advancement of the MLIR-based backend compiler stack for the CUTLASS Python DSL by designing dialects and associated compiler passes. * Author example kernels utilizing CUTLASS ...

Senior Software Engineer, CUTLASS Platform

Durham, NC · On-site

$118K - $156K/yr

Contribute to the advancement of the MLIR-based backend compiler stack for the CUTLASS Python DSL by designing dialects and associated compiler passes. * Author example kernels utilizing CUTLASS ...

The Mission We are building an MLIR-based compiler and inference stack for custom AI silicon used in telecommunications baseband processing. The compiler takes ML models from StableHLO through ...

The Mission We are building an MLIR-based compiler and inference stack for custom AI silicon used in telecommunications baseband processing. The compiler takes ML models from StableHLO through ...

Senior Software Engineer, CUTLASS Platform

Austin, TX · On-site

$121K - $160K/yr

Contribute to the advancement of the MLIR-based backend compiler stack for the CUTLASS Python DSL by designing dialects and associated compiler passes. * Author example kernels utilizing CUTLASS ...

Showing results 41-60

Mlir information

What is MLIR?

MLIR (Multi-Level Intermediate Representation) is an open-source compiler infrastructure project developed by the LLVM community. It provides a flexible and extensible intermediate representation framework, which is used to build reusable and modular compiler components for a wide range of domains, such as machine learning, hardware acceleration, and domain-specific languages. MLIR enables developers to create custom dialects and transformations, making it easier to optimize and target various hardware architectures. Its primary goal is to facilitate the development of high-performance and portable compilers.

What skills and qualifications are needed to work with MLIR?

To thrive as an MLIR developer, you need a strong background in compiler theory, C++ programming, and familiarity with LLVM infrastructure, typically supported by a degree in computer science or a related field. Experience with tools such as the MLIR framework, LLVM, and related build systems like CMake is highly valuable. Analytical thinking, problem-solving, and effective collaboration are important soft skills for innovating and working within open-source or cross-functional teams. These skills ensure the efficient design and optimization of compiler components, driving advancements in machine learning and hardware support.

How does an engineer working with MLIR collaborate with different teams?

Engineers specializing in MLIR (Multi-Level Intermediate Representation) often work closely with compiler teams, hardware architects, and machine learning researchers to optimize and integrate new features. Collaboration frequently involves participating in design discussions, code reviews, and cross-functional meetings to align on performance goals and implementation strategies. These engineers also contribute to open-source projects and may mentor junior team members or coordinate with external contributors. Working in such a dynamic and interdisciplinary environment helps ensure that MLIR tools remain robust, efficient, and aligned with evolving hardware and ML frameworks.

What is the difference between Mlir vs Machine Learning Engineer?

AspectMlirMachine Learning Engineer
Required CredentialsTechnical knowledge of compiler infrastructure, programming skills in C++/PythonDegree in Computer Science, Data Science, or related fields; experience with ML frameworks
Work EnvironmentResearch and development in compiler and software infrastructure teamsDeveloping, testing, and deploying machine learning models in various industries
Employer & Industry UsageTech companies, AI research labs, compiler development firmsTech companies, startups, AI-focused organizations
Common Search & Comparison IntentUnderstanding technical roles in compiler infrastructureLearning about careers in machine learning and AI

While Mlir focuses on compiler infrastructure and software development for optimizing machine learning models, Machine Learning Engineers primarily design and implement ML models for practical applications. Both roles require technical expertise, but Mlir is more specialized in compiler technology, whereas Machine Learning Engineers work directly on AI solutions.

More about Mlir jobs

What cities are hiring for Mlir jobs?

Cities with the most Mlir job openings:

What states have the most Mlir jobs?

States with the most job openings for Mlir jobs include:

Infographic showing various Mlir job openings in the United States as of August 2026, with employment types broken down into 99% Full Time, and 1% Contract. Highlights an 78% Physical, 6% Hybrid, and 16% Remote job distribution.

Senior Software Engineer, CUTLASS Platform

Nvidia

Santa Clara, CA

$143K - $189K/yr

Full-time

Re-posted 6 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies


Job description

NVIDIA's high-performance computing platforms are powering the AI revolution across many applications and industries. Within our software stack, CUTLASS stands out as a popular open-source ecosystem dedicated to high-performance linear algebra and Tensor Core primitives. Since 2017, it has provided the community with C++ and Python abstractions to implement custom matrix multiply (GEMM) and related math and deep learning computations on NVIDIA GPUs.

If you are passionate about designing abstractions for Tensor Core and related GPU hardware features in MLIR, Python, and C++ that enable writing high performance kernels, apply to join the CUTLASS team today. What you'll be doing: Develop core components of the CUTLASS platform including Tensor Core MMAs, copies, synchronization barriers, schedulers, and other GPU hardware features in CUDA C++ and CUTLASS Python DSL. Contribute to the advancement of the MLIR-based backend compiler stack for the CUTLASS Python DSL by designing dialects and associated compiler passes.

Author example kernels utilizing CUTLASS abstractions to showcase the use of novel GPU hardware features that are crucial for achieving high performance. Collaborate with GPU architecture, CUDA, and NVVM/PTX compiler teams to provide feedback on programming models and to assess the performance of future GPU hardware features. What we need to see: Masters or PhD degree in Computer Science, Computer Engineering, or related field (or equivalent experience).

3+ years of relevant industry experience. Strong proficiency in C++ programming and software design, including debugging, performance evaluation, and testing. Experience working with high-performance code generation and knowledge of compiler transformations and optimizations.

A deep understanding of computer architecture and parallel computing programming models. Ways to stand out from the crowd: Experience writing high-performance kernels at low levels of abstractions like NVVM/ PTX for GPUs or other similar parallel processing architectures. Hands-on compiler design experience, particularly in MLIR.

Understanding of deep learning models, algorithms, and frameworks. NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hard working people in the world working for us.

If you're creative, autonomous, and love a challenge, consider joining our Deep Learning Library team and help us build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field. 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 for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits. Applications for this job will be accepted at least until June 5, 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.


What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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About Nvidia

Sourced by ZipRecruiter

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.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US