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Machine Learning Compiler Engineer Jobs in California

Senior Compiler Engineer - AI

Santa Clara, CA · On-site

$143K - $189K/yr

We are seeking an AI Compiler Engineer with deep expertise in compiler technologies to join our ... The ideal candidate brings broad experience across machine learning, including reinforcement ...

Senior Compiler Engineer - AI

Santa Clara, CA · On-site

$143K - $189K/yr

We are seeking an AI Compiler Engineer with deep expertise in compiler technologies to join our ... The ideal candidate brings broad experience across machine learning, including reinforcement ...

Showing results 41-60

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

Burlingame, CA

quadric, Inc
Semiconductor and Electronic Component Manufacturing • 11 - 50 employees

$110K - $270K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 18 days ago


Job description

Quadric has created an innovative general purpose neural processing unit (GPNPU) architecture. Quadric's co-optimized software and hardware is targeted to run neural network (NN) inference workloads in a wide variety of edge and endpoint devices, ranging from battery operated smart-sensor systems to high-performance automotive or autonomous vehicle systems. Unlike other NPUs or neural network accelerators in the industry today that can only accelerate a portion of a machine learning graph, the Quadric GPNPU executes both NN graph code and conventional C++ DSP and control code.

Role

As a senior member of our platform software engineering team, you will be tasked with lowering and optimizing neural networks on the quadric EPU. You will design and implement algorithmic optimizations to extract maximum performance out of the Quadric architecture.


Responsibilities
  • Drive the lowering and optimization of cutting edge deep neural networks using Quadric's technology
  • Apply your skills and expertise in mathematical & algorithmic optimization toward solving NP-hard problems
  • Collaborate within the software team to develop algorithms that optimize graph-based execution on the Quadric architecture

Requirements

  • MS or Ph.D. in Computer Science, or related field, with a minimum of eight years of experience in the industry
  • Strong background in numerical and/or algorithmic optimization
  • Understanding of building application-appropriate heuristics for NP-hard problems
  • Knowledge of both classical as well as ML algorithms, e.g., Computer Vision, DSP, DNNs, etc.
  • Strong background in graphs and related algorithms
Nice to haves
  • Proficiency in C++ >= 11
  • Experience using / developing in TVM
  • Knowledge of front-end and back-end compiler techniques

Expected Outcomes in 12 months
  • Develop a deep understanding of the hardware platform and low level software and leverage that for optimal performance of applications.
  • Have a proven track record of implementing optimization passes for efficient lowering of deep learning and high performance computing algorithms on the Quadric EPU parallel processor.

Benefits

At Quadric, we value Integrity, Humility, and Happiness. What we expect from one another is simple and clear: Initiative, Collaboration, and Completion. We are a collaborative team focused on building something extraordinary in the edge computing space. 

  • Competitive salary and meaningful equity
  • Medical, dental, and vision plan options starting on day one
  • 401(k) retirement plan
  • Flexible paid time off (unlimited, non-accrual) to support work-life balance
  • When working in-office, enjoy company-provided lunches and a stocked kitchen
  • Convenient office location within walking distance of the Caltrain station
  • Support for commuting, including monthly parking or Caltrain passes
  • Downtown Burlingame office location, close to shops, cafes, and local amenities
  • A politics-free, highly collaborative environment where talented people can do their best work and make an immediate impact
  • The opportunity to build long-term career relationships in a company that values strong personal connections alongside professional excellence

The base salary range for this position is $110,000 to $270,000. This range reflects the full span of levels and geographies at which Quadric hires for this role. The actual base salary offered will depend on a number of factors, including the specific level of the role, years and depth of relevant experience, technical skills and competencies, the criticality of the role to the business, internal equity, and work location. In addition to base salary, this role is eligible for equity and a discretionary annual performance bonus as applicable to the role and level. 

Quadric also offers the generous benefits package outlined above and other programs designed to support your health and wellbeing.

Founded in 2016 and based in downtown Burlingame, California, Quadric is building the world's first supercomputer designed for the real-time needs of edge devices. Quadric aims to empower developers in every industry with superpowers to create tomorrow's technology, today. The company was co-founded by technologists from MIT and Carnegie Mellon, who were previously the technical co-founders of the Bitcoin computing company 21.

Quadric is proud to be an equal opportunity employer. We are committed to creating an inclusive environment where people from all backgrounds can do their best work. We consider all qualified applicants without regard to race, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic under applicable law.

If this role resonates with you, we encourage you to apply even if your experience does not perfectly match every qualification. We value potential, curiosity, and a willingness to learn just as much as direct experience. Skills and growth come in many forms, and we would love to hear your story.

By submitting an application, you acknowledge that Quadric will collect and process your personal information as part of the hiring process. Please review our Privacy Policy to understand how we handle your data.


Quadric.io logo

About Quadric.io

Sourced by ZipRecruiter

Industry

Semiconductor and electronic component manufacturing

Company size

11 - 50 Employees

Headquarters location

Burlingame, CA, US

Year founded

2016

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