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Mlir Jobs (NOW HIRING)

Mythic

Compiler Engineer - MLIR / PyTorch Infrastructure

$110K - $144K/yr

The role involves advancing the MLIR ecosystem by architecting compiler flows, building conversion paths, and extending MLIR integration across various systems. Responsibilities : • Architect the ...

Mythic

Compiler Engineer - MLIR / PyTorch Infrastructure

$110K - $144K/yr

The role involves advancing the MLIR ecosystem by architecting compiler flows and enhancing interoperability with PyTorch and other frameworks. Responsibilities : • Architect the migration of the ...

DensityAI

Compiler Engineer -- MLIR

Mountain View, CA · On-site

Responsibilities : • Own MLIR dialect design and lowering passes for our AI accelerator -- defining the high-level tensor IR, async / streaming semantics, and sharded-tensor types that bridge ML ...

Mythic

Compiler Engineer - MLIR / PyTorch Infrastructure

$110K - $144K/yr

The Compiler Engineer will advance the MLIR ecosystem by extending existing high-level dialects and designing a new hardware-aware low-level dialect, working closely with hardware engineers and ML ...

Mythic

Compiler Engineer - MLIR / PyTorch Infrastructure

$110K - $144K/yr

The Compiler Engineer will advance the MLIR ecosystem by architecting the migration of the existing compiler flow into MLIR and building conversion paths, working closely with hardware engineers and ...

DensityAI

Compiler Engineer - MLIR

Mountain View, CA

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

About the role Own MLIR dialect design and lowering passes for our AI accelerator - defining the high-level tensor IR, async / streaming semantics, and sharded-tensor types that bridge ML frameworks ...

DensityAI

Compiler Engineer -- MLIR

Mountain View, CA

$200K - $360K/yr

About the role Own MLIR dialect design and lowering passes for our AI accelerator -- defining the high-level tensor IR, async / streaming semantics, and sharded-tensor types that bridge ML frameworks ...

DensityAI

Compiler Engineer - MLIR

Mountain View, CA · On-site

$200K - $360K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

About the role Own MLIR dialect design and lowering passes for our AI accelerator - defining the high-level tensor IR, async / streaming semantics, and sharded-tensor types that bridge ML frameworks ...

Nvidia

Senior AI Compiler Engineer, MLIR

Austin, TX

$121K - $160K/yr

Develop MLIR-based graph representations and optimizations for future GPU architectures. * Partner with framework and hardware teams to enable new model patterns and upcoming GPU architectural ...

New

Nvidia

Senior AI Compiler Engineer, MLIR

Seattle, WA

$139K - $183K/yr

Develop MLIR-based graph representations and optimizations for future GPU architectures. * Partner with framework and hardware teams to enable new model patterns and upcoming GPU architectural ...

New

Nvidia

Senior AI Compiler Engineer, MLIR

Santa Clara, CA

$143K - $189K/yr

Develop MLIR-based graph representations and optimizations for future GPU architectures. * Partner with framework and hardware teams to enable new model patterns and upcoming GPU architectural ...

New

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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.

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.

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.
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Mlir jobs near you
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 81% Physical, 5% Hybrid, and 14% Remote job distribution.

Compiler Engineer - MLIR / PyTorch Infrastructure

Mythic

Remote

$110K - $144K/yr

Full-time

Re-posted 27 days ago

Job description

Job Summary:
Mythic is building the future of AI computing with breakthrough analog technology. The role involves advancing the MLIR ecosystem by architecting compiler flows, building conversion paths, and extending MLIR integration across various systems.
Responsibilities:
• Architect the migration of the existing compiler flow into MLIR, defining dialects, passes, and lowering strategies.
• Build conversion paths between MLIR and Mythic’s custom low-level IR to keep both flows operational during migration.
• Define validation infrastructure within MLIR, including interpretation or execution paths for simulation and debugging.
• Enable compilation by extending MLIR integration across analog accelerators and digital subsystems.
• Leverage Torch-MLIR where PyTorch inputs are available, and guide future integration with PyTorch 2.0 compiler technologies (TorchInductor, TorchDynamo, Torch-MLIR)
Qualifications:
Required:
• 3+ years of experience in compiler or high-performance systems development.
• Proficiency in modern C++ (C++14/17/20) and Python.
• Direct, hands-on experience with MLIR, including dialect design, compiler passes, or lowering pipelines.
• Strong understanding of compiler IRs and transformations, with the ability to reason about lowering from high-level ops to hardware-aware representations.
Preferred:
• Experience architecting complete MLIR flows: from frontend dialects down to hardware-aware dialects, including conversion to and from existing IRs.
• Familiarity with PyTorch compiler technologies, especially Torch-MLIR and integration paths with PyTorch 2.0 (TorchDynamo, TorchInductor).
• Knowledge of dataflow architectures, scheduling, and memory orchestration.
• Background in heterogeneous or specialized accelerators (e.g., analog compute, NPUs, GPUs, DSPs).
Company:
Mythic develops analog matrix processors and key cards based on analog compute-in-memory. Founded in 2012, the company is headquartered in Austin, USA, with a team of 51-200 employees. The company is currently Early Stage.

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