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Mlir Engineer Jobs (NOW HIRING)

DensityAI

Compiler Engineer -- MLIR

Mountain View, CA

$200K - $360K/yr

Exceptional abilities in MLIR dialect design, lowering pass authoring, and rewrite patterns * 5+ years compiler engineering experience, with hands-on MLIR contributions or equivalent IR-design ...

NVIDIA

Senior AI Compiler Engineer, MLIR

Seattle, WA · On-site

$139K - $183K/yr

NVIDIA is known as 'the AI computing company' and is hiring a Senior AI Compiler Engineer. The role involves building an MLIR-based AI compiler that enhances NVIDIA's inference engine, focusing on ...

Nvidia

Senior AI Compiler Engineer, MLIR

Santa Clara, CA

$143K - $189K/yr

NVIDIA is hiring a Senior AI Compiler Engineer. GPUs are driving rapid progress in deep learning-from LLMs and generative AI to recommendation, vision, and speech. On this team, you'll build an MLIR ...

Nvidia

Senior AI Compiler Engineer, MLIR

Seattle, WA · On-site

$139K - $183K/yr

NVIDIA is hiring a Senior AI Compiler Engineer. GPUs are driving rapid progress in deep learning-from LLMs and generative AI to recommendation, vision, and speech. On this team, you'll build an MLIR ...

Nvidia

Senior AI Compiler Engineer, MLIR

Austin, TX

$121K - $160K/yr

NVIDIA is hiring a Senior AI Compiler Engineer. GPUs are driving rapid progress in deep learning-from LLMs and generative AI to recommendation, vision, and speech. On this team, you'll build an MLIR ...

Nvidia

OR

$122K - $161K/yr

NVIDIA is hiring a Senior AI Compiler Engineer. GPUs are driving rapid progress in deep learning-from LLMs and generative AI to recommendation, vision, and speech. On this team, you'll build an MLIR ...

Ericsson

Senior AI Compiler Engineer

Austin, TX · On-site

$103K - $142K/yr

MLIR Architecture | Compiler Infrastructure | 5G/6G Silicon | Bare-Metal AI The Mission Most AI compiler engineers optimize models for GPUs that already exist. You're going to optimize them for ...

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Mlir Engineer information

What is the difference between Mlir Engineer vs Compiler Engineer?

AspectMlir EngineerCompiler Engineer
Required CredentialsBachelor's or Master's in Computer Science, experience with MLIR, compiler frameworksBachelor's or Master's in Computer Science, strong programming skills, compiler theory knowledge
Work EnvironmentResearch labs, tech companies focusing on AI/ML, compiler development teamsSoftware development firms, tech companies, open-source projects
Industry UsageAI/ML hardware optimization, compiler infrastructure, MLIR frameworkSoftware optimization, language development, system software

Both roles involve working with compiler technologies, but Mlir Engineers specialize in the MLIR framework and its applications in AI/ML hardware optimization, while Compiler Engineers focus broadly on compiler design and implementation across various software systems.

What are the key skills and qualifications needed to thrive as an MLIR Engineer, and why are they important?

To thrive as an MLIR Engineer, you need a solid background in compiler theory, C++ programming, and experience with machine learning frameworks or intermediate representations. Familiarity with LLVM, the MLIR ecosystem, and version control systems like Git is typically required, as well as a relevant degree in computer science or a related field. Strong problem-solving skills, attention to detail, and effective communication are valuable soft skills in this role. These qualifications and skills are crucial for building robust compiler infrastructure, collaborating across teams, and ensuring efficient support for diverse machine learning workloads.

What are some common challenges faced by MLIR Engineers when integrating new dialects into existing compiler infrastructures?

MLIR Engineers often encounter challenges such as ensuring compatibility between new dialects and existing IR components, maintaining performance optimizations, and avoiding redundancy or conflicts in transformations. Integrating a new dialect requires deep understanding of both the MLIR ecosystem and the target hardware or frameworks, which can be complex due to rapid evolution in machine learning compilers. Close collaboration with backend and frontend teams is essential to address integration issues and to ensure that new dialects meet project requirements and performance goals.

What is an MLIR Engineer?

An MLIR Engineer is a software engineer who specializes in working with the Multi-Level Intermediate Representation (MLIR) compiler framework. MLIR is an open-source project designed to provide a flexible and extensible infrastructure for building domain-specific compilers and optimizing machine learning workloads. MLIR Engineers typically design, implement, and optimize compiler passes, dialects, and transformations to improve the performance and portability of machine learning models across different hardware architectures. They often collaborate with machine learning researchers, compiler engineers, and hardware teams to enable efficient model deployment.
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Compiler Engineer - MLIR / PyTorch Infrastructure

Compiler Engineer - MLIR / PyTorch Infrastructure

Mythic

Austin, TX • On-site

$106K - $139K/yr

Full-time

Posted 9 days ago

Job description

About us
Mythic is building the future of AI computing with breakthrough analog technology that delivers 100 the performance of traditional digital systems at the same power and cost. This unlocks bigger, more capable models and faster, more responsive applications-whether in edge devices like drones, robotics, and sensors, or in cloud and data center environments. Our technology powers everything from large language models and CNNs to advanced signal processing, and is engineered to operate from -40 C to +125 C, making it ideal for industrial, automotive, aerospace, and defense.

We've raised over $100M from world-class investors including Softbank, Threshold Ventures, Lux Capital, and DCVC, and secured multi-million-dollar customer contracts across multiple markets.

About the role
Join us in advancing the MLIR ecosystem at Mythic. You'll help extend our existing high-level dialects and design a new hardware-aware low-level dialect, building conversion paths that bridge to our current IRs. Working closely with hardware engineers and ML developers, your work will expand interoperability with PyTorch and other frameworks, laying the groundwork for long-term innovation. The result: an MLIR-based stack that unifies hardware constraints with developer needs and accelerates adoption of modern ecosystems.
Here's what you will do
  • 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)
Here's the background we hope you will have
  • 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.
The following would be nice to have, but is not required
  • 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).
What we offer
  • Shape the MLIR and PyTorch integration strategy for novel AI hardware.
  • Opportunity to contribute upstream and influence the broader ML compiler ecosystem.
  • Collaborate with a team spanning hardware, runtime, and compiler design.
  • Competitive compensation, equity, and comprehensive benefits.
At Mythic, we foster a collaborative and respectful environment where people can do their best work. We hire smart, capable individuals, provide the tools and support they need, and trust them to deliver. Our team brings a wide range of experiences and perspectives, which we see as a strength in solving hard problems together. We value professionalism, creativity, and integrity, and strive to make Mythic a place where every employee feels they belong and can contribute meaningfully.
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