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Remote Machine Learning Compiler Engineer Jobs in San Francisco, CA

quadric, Inc

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 ...

Unitytech

Machine Learning Engineer

San Francisco, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ... Mountain View, SF/Bay: $117,000 - $152,000 gross USD Bellevue, Seattle, NYC, Remote CA: $104,100 ...

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site +1

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site +1

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Canals

Machine Learning Engineer

San Francisco, CA · Remote

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining ... We're remote-first, flexible, and distributed across North and South America, bringing together ...

Freenome

Senior Machine Learning Engineer

Brisbane, CA · On-site +1

$147K - $194K/yr

At Freenome, we are seeking a Senior Machine Learning Research Engineer to join the Machine ... remote. What you'll do: * Implement and refine DL pipelines on distributed computing platforms ...

Capital One

Lead Machine Learning Engineer

San Francisco, CA · On-site +1

$120K - $159K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

EvenUp

Staff Machine Learning Engineer

San Francisco, CA · Remote

$212K - $301K/yr

Join EvenUp as a Staff Machine Learning Engineer and help set the technical direction for how ... Open to remote candidates or 3 days a week hybrid from our Toronto or San Francisco hubs. Benefits ...

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Remote Machine Learning Compiler Engineer information

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$88.4K

$197.3K

$241.5K

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

As of Aug 11, 2026, the average yearly pay for remote machine learning compiler engineer in San Francisco, CA is $197,270.00, according to ZipRecruiter salary data. Most workers in this role earn between $168,500.00 and $241,500.00 per year, depending on experience, location, and employer.

How does a remote machine learning compiler engineer typically collaborate with cross-functional teams to optimize model deployment?

As a Remote Machine Learning Compiler Engineer, you will frequently collaborate with data scientists, hardware engineers, and software developers to ensure that machine learning models are efficiently compiled and deployed on target platforms. Communication often takes place through virtual meetings, code reviews, and shared documentation tools. You'll be responsible for translating research models into optimized code, troubleshooting performance bottlenecks, and integrating feedback from various stakeholders. Effective teamwork is crucial, as the success of deployments often depends on iterative feedback and close alignment with both the ML research and hardware teams.

What is a remote machine learning compiler engineer?

A Remote Machine Learning Compiler Engineer is a software engineer who specializes in developing and optimizing compilers specifically for machine learning workloads, while working from a remote location. Their primary responsibilities include designing and implementing compiler features that translate machine learning models into efficient code for various hardware platforms, such as CPUs, GPUs, or specialized accelerators. They collaborate closely with machine learning researchers, hardware engineers, and software developers to ensure high performance and compatibility. In addition to strong programming skills, they typically require expertise in compiler theory, machine learning frameworks, and hardware architectures. This role allows for flexible, location-independent work while contributing to cutting-edge AI technologies.

What is the difference between Remote Machine Learning Compiler Engineer vs Remote Data Scientist?

AspectRemote Machine Learning Compiler EngineerRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Software Engineering, or related fields; knowledge of compiler design and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming, statistics, and data analysis
Work EnvironmentPrimarily software development, compiler optimization, and ML model deploymentData analysis, model building, and interpretation of results
Industry UsageTech companies, AI startups, hardware firms focusing on ML hardware accelerationTech, finance, healthcare, and research organizations

While both roles involve working with machine learning, the Remote Machine Learning Compiler Engineer focuses on developing and optimizing compilers for ML models, whereas the Remote Data Scientist concentrates on analyzing data and building predictive models. The roles share some technical skills but differ in their core responsibilities and work environments.

What are the key skills and qualifications needed to thrive as a remote machine learning compiler engineer, and why are they important?

To thrive as a Remote Machine Learning Compiler Engineer, you need a strong background in computer science, proficiency in programming languages like C++ and Python, and expertise in compiler theory and machine learning frameworks. Familiarity with ML compilers such as TVM or XLA, and experience using version control and CI/CD systems are commonly required, along with a relevant bachelor's or master's degree. Outstanding problem-solving, collaboration, and communication skills are essential for working effectively in distributed teams and across technical domains. These skills and qualities enable the development of efficient, scalable ML solutions that bridge software and hardware, ensuring high performance and innovation.
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Remote Machine Learning Compiler Engineer jobs near you

Deep Learning Compiler Engineer

quadric, Inc

Burlingame, CA • On-site, Remote

$110K - $270K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 7 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.
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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

Social media

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