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Machine Learning Compiler Engineer Jobs (NOW HIRING)

Qualcomm

Machine Learning Compiler

Raleigh, NC · On-site

$160K - $240K/yr

Engineering Group, Engineering Group > Machine Learning Engineering General Summary: Lead a team of engineers focused on advancing machine learning compiler technologies for cutting-edge AI ...

Nvidia

Senior AI Compiler Engineer

Austin, TX · On-site

$103K - $142K/yr

We are seeking a Machine Learning Compiler Engineer with deep expertise in compiler technologies to join our team. The ideal candidate will bring broad experience across the machine learning ...

SEMRON

Compiler Developer

Austin, TX · On-site

SEMRON is redefining what's possible in AI hardware, and they are seeking a Compiler Developer to ... machine learning compiler infrastructure like MLIR/IREE or TVM • experience in polyhedral ...

Nvidia

Senior AI Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

We are seeking a Machine Learning Compiler Engineer with deep expertise in compiler technologies to join our team. The ideal candidate will bring broad experience across the machine learning ...

Nvidia Corporation

Senior AI Compiler Engineer

Austin, TX · On-site

$103K - $142K/yr

We are seeking a Machine Learning Compiler Engineer with deep expertise in compiler technologies to join our team. The ideal candidate will bring broad experience across the machine learning ...

Nvidia

OR · On-site

$104K - $143K/yr

We are seeking a Machine Learning Compiler Engineer with deep expertise in compiler technologies to join our team. The ideal candidate will bring broad experience across the machine learning ...

Nvidia

Senior AI Compiler Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

We are seeking a Machine Learning Compiler Engineer with deep expertise in compiler technologies to join our team. The ideal candidate will bring broad experience across the machine learning ...

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Machine Learning Compiler Engineer information

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$31.5K

$128.8K

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How much do machine learning compiler engineer jobs pay per year?

As of Jun 7, 2026, the average yearly pay for machine learning compiler engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What is a Machine Learning Compiler Engineer job?

A Machine Learning Compiler Engineer focuses on optimizing and building compilers that translate high-level machine learning models into efficient code runnable on specialized hardware (e.g., GPUs, TPUs). They work on improving performance, memory usage, and execution efficiency of ML workloads by designing compiler optimizations, code generation techniques, and leveraging frameworks like LLVM or MLIR. Their role bridges the gap between ML researchers and hardware engineers, ensuring models run efficiently on target platforms.

What are the typical daily responsibilities of a Machine Learning Compiler Engineer?

As a Machine Learning Compiler Engineer, your daily responsibilities often include designing and implementing new compiler optimizations, collaborating with machine learning researchers to support model deployment, and debugging performance or correctness issues in compiled code. You may participate in code reviews, write technical documentation, and conduct benchmarking to evaluate how machine learning models perform on various hardware backends. Close collaboration with hardware engineers, software architects, and data scientists is common, ensuring end-to-end solutions meet both research and production requirements. Staying updated with the latest advancements in both compiler technology and machine learning frameworks is also a key aspect of the role.

What are the key skills and qualifications needed to thrive in the Machine Learning Compiler Engineer position, and why are they important?

A Machine Learning Compiler Engineer needs a deep understanding of computer science fundamentals, compiler theory, and experience with machine learning frameworks, often supported by a relevant degree in computer science or engineering. Proficiency with tools such as LLVM, TVM, MLIR, and languages like C++, Python, and CUDA is typically required, and familiarity with hardware architectures is a plus. Strong problem-solving, teamwork, and communication skills are essential for collaborating with cross-functional teams and addressing complex system issues. These capabilities are important for designing and optimizing compilers that enable scalable and efficient deployment of machine learning models on diverse hardware platforms.

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Machine Learning Compiler Engineer jobs near you
Infographic showing various Machine Learning Compiler Engineer job openings in the United States as of May 2026, with employment types broken down into 1% Locum Tenens, 93% Full Time, 2% Part Time, 2% Contract, and 2% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.
Machine Learning - Compiler Engineer II, Annapurna Labs

Machine Learning - Compiler Engineer II, Annapurna Labs

Amazon

Seattle, WA • On-site

Full-time

Posted 25 days ago

Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,820 frontline employees who took The Breakroom Quiz

7th of 39 rated national retailers

Job description

The Product: AWS Machine Learning accelerators are at the forefront of AWS innovation and one of several AWS tools used for building Generative AI on AWS. The Inferentia chip delivers best-in-class ML inference performance at the lowest cost in cloud. Trainium will deliver the best-in-class ML training performance with the most teraflops (TFLOPS) of compute power for ML in the cloud.

This is all enabled by cutting edge software stack, the AWS Neuron Software Development Kit (SDK), which includes an ML compiler, runtime and natively integrates into popular ML frameworks, such as PyTorch, TensorFlow and MxNet. AWS Neuron and Inferentia are used at scale with customers like Snap, Autodesk, Amazon Alexa, Amazon Rekognition and more customers in various other segments.
The Team: As a whole, the Amazon Annapurna Labs team is responsible for silicon development at AWS. The team covers multiple disciplines including silicon engineering, hardware design and verification, software and operations.
The AWS Neuron team works to optimize the performance of complex neural net models on our custom-built AWS hardware

More specifically, the AWS Neuron team is developing a deep learning compiler stack that takes neural network descriptions created in frameworks such as TensorFlow, PyTorch, and MXNET, and converts them into code suitable for execution. As you might expect, the team is comprised of some of the brightest minds in the engineering, research, and product communities, focused on the ambitious goal of creating a toolchain that will provide a quantum leap in performance.
You: Machine Learning Compiler Engineer II on the AWS Neuron team, you will be supporting the ground-up development and scaling of a compiler to handle the world's largest ML workloads. Architecting and implementing business-critical features, publish cutting-edge research, and contributing to a brilliant team of experienced engineers excites and challenges you

You will leverage your technical communications skill as a hands-on partner to AWS ML services teams and you will be involved in pre-silicon design, bringing new products/features to market, and many other exciting projects.
A background in Machine Learning and AI accelerators is preferred, but not required.
About the team
About Us
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion

We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon's culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Work/Life Balance
Our team puts a high value on work-life balance

It isn't about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members

We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.
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What Amazon employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US

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