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Machine Learning Compiler Engineer Jobs in California

Our Compiler team is responsible for constructing and emitting the highest performance GPU machine ... deep-learning compiler technology spanning architecture design and support through functional ...

Our Compiler team is responsible for constructing and emitting the highest performance GPU machine ... Be part of a team that is at the center of deep-learning compiler technology spanning architecture ...

Compiler Engineer

San Jose, CA · On-site

$160K - $300K/yr

Design, develop, and maintain compiler toolchains that translate machine learning models from ... Collaborate closely with machine learning engineers to support model conversion, validation ...

Senior Compiler Engineer

San Jose, CA · On-site

$160K - $210K/yr

The Compiler Engineer will contribute to the design and implementation of an embedded machine learning (ML) system stack and TinyML applications to run on the world's most energy-efficient ...

Senior Code Generator Compiler Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

Our Compiler team is responsible for constructing and emitting the highest performance GPU machine ... deep-learning compiler technology spanning architecture design and support through functional ...

Deep Learning Compiler Engineer

Burlingame, CA · On-site +1

$110K - $270K/yr

... a portion of a machine learning graph, the Quadric GPNPU executes both NN graph code and ... Role As a senior member of our platform software engineering team, you will be tasked with lowering ...

Showing results 21-40

Machine Learning Compiler Engineer information

See California salary details

$31.1K

$127.1K

$191K

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

As of Sep 10, 2026, the average yearly pay for machine learning compiler engineer in California is $127,083.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,200.00 and $153,000.00 per year, depending on experience, location, and employer.

What is a machine learning compiler engineer?

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 as a machine learning compiler engineer?

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.

What are the most commonly searched types of Machine Learning Compiler Engineer jobs in California?

The most popular types of Machine Learning Compiler Engineer jobs in California are:

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

The top searched job categories for Machine Learning Compiler Engineer jobs in California are:

Infographic showing various Machine Learning Compiler Engineer job openings in California as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $127,083 per year, or $61.1 per hour.

Deep Learning Compiler Engineer

Santa Clara, CA

Nvidia
Computer and Electronic Product Manufacturing • 10K+ employees

Full-time

Posted 21 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz


Job description

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. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work.

Come join the team and see how you can make a lasting impact on the world. We are hiring software engineers for the Tensor IR & CUDA Tile team. NVIDIA GPUs are at the center of the deep learning revolution and continue to enable breakthroughs in generative AI, large language models, recommendation systems, speech recognition, image classification and other areas.

Come join us to work with a top-notch team and have broad impact across the entire deep learning community. What you'll be doing: In this role, you will work on CUDA Tile and TensorIR compiler technologies for NVIDIA GPUs. CUDA Tile is a new tile-based programming model that shipped with CUDA 13.1, and TensorIR is an open-source compiler infrastructure project that uses CUDA Tile to generate high-performance GPU kernels

You will design and implement compiler transformations, develop MLIR-based dialects and lowering passes, and optimize the performance of tile-based kernels to ensure they execute efficiently across multiple generations of NVIDIA GPU architectures. The scope of these efforts includes defining public APIs, crafting and implementing compiler and optimization techniques, performance optimization, and other general software engineering work. What we need to see: Bachelors, Masters or Ph.D

in Computer Science, Computer Engineering or a related field (or equivalent experience) 3+ years of relevant work or research experience in compiler optimization, performance analysis and IR design. Ability to work independently, define project goals and scope, and lead your own development effort. Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design.

Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team. Ways to stand out from the crowd: Knowledge of CPU and/or GPU architecture. CUDA or OpenCL programming experience.

Experience with the following technologies: MLIR, LLVM, XLA, TVM and deep learning models and algorithms. With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles.

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. You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 27, 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. #deeplearning.


What Nvidia employees say

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Benefits

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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