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Ml Compiler Engineer Jobs in California (NOW HIRING)

Nvidia

Senior Compiler Engineer Infrastructure

Santa Clara, CA · On-site +1

$127K - $173K/yr

Our compiler organization makes its mark on every GPU NVIDIA produces. By improving how our ... Practical experience applying AI or ML-based tools to improve engineering workflows * Background in ...

Persimmons

Compiler Engineer (Frontend)

San Jose, CA · On-site

Design and build the compiler that converts AI models from popular ML frameworks into assembly code ... Provide technical leadership across the compiler team, mentoring engineers in advanced compiler ...

Persimmons

Compiler Engineer (Frontend)

San Jose, CA

Design and build the compiler that converts AI models from popular ML frameworks into assembly code ... Provide technical leadership across the compiler team, mentoring engineers in advanced compiler ...

Persimmons

Compiler Engineer (Frontend)

San Jose, CA · On-site

Design and build the compiler that converts AI models from popular ML frameworks into assembly code ... Provide technical leadership across the compiler team, mentoring engineers in advanced compiler ...

DensityAI

Compiler Engineer -- MLIR

Mountain View, CA · On-site

$200K - $360K/yr

... compiler engineering experience, with hands-on MLIR contributions or equivalent IR-design ... Strong C++ fluency and experience integrating with ML frameworks (PyTorch, JAX, ONNX, TensorFlow ...

Lemurian Labs

Front End Compiler

Santa Clara, CA

About the Role We're looking for a Front End Compiler Engineer to own the ingestion layer of our ... Contribute to documentation and tooling that helps ML engineers understand and debug the ingestion ...

Lemurian Labs

Front End Compiler

Santa Clara, CA · On-site

... ML engineers understand and debug the ingestion process Qualifications : Required : • BS degree in Computer Science or equivalent practical experience • 2+ years of experience working with ML ...

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Ml Compiler Engineer information

What does an ML Compiler Engineer do?

An ML Compiler Engineer designs and develops compilers and software tools that optimize machine learning models for deployment on various hardware platforms. Their work involves translating high-level ML code into optimized, low-level instructions that can run efficiently on CPUs, GPUs, or specialized accelerators. They collaborate closely with hardware engineers and ML researchers to ensure models execute quickly and accurately. Additionally, ML Compiler Engineers may work on improving performance, reducing memory usage, and supporting new ML frameworks or hardware.

What are some typical collaboration points between an ML Compiler Engineer and other teams during a project?

ML Compiler Engineers frequently collaborate with machine learning researchers to understand model requirements, with hardware engineers to optimize for specific accelerators, and with software developers to ensure seamless integration into production systems. This role often involves participating in cross-functional meetings, code reviews, and design discussions to align compiler optimizations with both hardware capabilities and end-user needs. Effective communication and teamwork are essential, as these engineers play a central role in bridging the gap between algorithm design and efficient execution on target platforms.

What is the difference between Ml Compiler Engineer vs Machine Learning Engineer?

AspectMl Compiler EngineerMachine Learning Engineer
Required SkillsProgramming, compiler design, optimization, ML frameworksData analysis, model development, programming, ML frameworks
Work EnvironmentResearch labs, tech companies, AI hardware firmsTech companies, startups, data-driven organizations
CertificationsComputer science, software engineering, specialized compiler coursesMachine learning, data science, AI certifications
Industry UsageAI hardware, software optimization, ML infrastructureModel development, deployment, data analysis

While both roles involve machine learning, Ml Compiler Engineers focus on optimizing ML models through compiler design and software performance, whereas Machine Learning Engineers develop and deploy ML models for applications. The roles often overlap in skills but differ in their primary focus areas.

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

To thrive as an ML Compiler Engineer, you need a strong background in computer science, compiler design, machine learning concepts, and typically a degree in computer science or a related field. Familiarity with tools like LLVM, MLIR, TensorFlow XLA, and programming in C++ and Python is often required, along with experience in optimizing machine learning workloads. Strong problem-solving abilities, attention to detail, and effective collaboration skills help set top professionals apart. These skills ensure efficient translation and optimization of ML models for diverse hardware, enhancing performance and scalability.

What are popular job titles related to Ml Compiler Engineer jobs in California?

For Ml Compiler Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Ml Compiler Engineer jobs in California look for?

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What cities in California are hiring for Ml Compiler Engineer jobs?

Cities in California with the most Ml Compiler Engineer job openings:

Ml Compiler Engineer jobs near you
Infographic showing various Ml Compiler Engineer job openings in California as of August 2026, with employment types broken down into 88% Full Time, 5% Part Time, 2% Temporary, and 5% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution.

Sr. Machine Learning - Compiler Engineer III, AWS Neuron, Annapurna Labs

Amazon

Cupertino, CA • On-site

$128K - $177K/yr

Full-time

Re-posted 26 days ago

Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 7,086 frontline employees who took The Breakroom Quiz

6th 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: As a Sr

Machine Learning Compiler Engineer III on the AWS Neuron team, you will be a thought leader 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 mentoring 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.
In order to be considered for this role, candidates must be currently located or willing to relocate to Cupertino (perferred), Seattle, Austin, or Toronto.
About the team
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.

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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