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Remote Machine Learning Compiler Engineer Jobs in Alameda, CA

MatX

Software Engineer - Compiler

Mountain View, CA · On-site +1

$175K - $400K/yr

Learning & Development $1,500 yearly towards your professional development e.g. conferences ... Remote Perks We work remotely Monday & Friday, supported by home-tech setup, and remote wifi ...

Freenome

Staff Machine Learning Scientist

Brisbane, CA · On-site +1

$199K - $283K/yr

... remote. What you'll do: * Independently pursue cutting edge research in AI applied to biological ... Work closely with ML Engineering partners to ensure that Freenome's computational infrastructure ...

Shipt

Staff Machine Learning Engineer

San Francisco, CA · On-site +1

Impact As a Staff Machine Learning Engineer on Shipt's Personalization Platform team you will drive key AI initiatives. In this role, you'll collaborate with Data Scientists to design and deploy ...

Freenome

Senior Machine Learning Scientist

Brisbane, CA · On-site +1

$110K - $150K/yr

... remote. What you'll do: * Independently pursue cutting edge research in AI applied to biological ... Work closely with ML Engineering partners to ensure that Freenome's computational infrastructure ...

S.T.E.P.

Senior Machine Learning Engineer

Palo Alto, CA · On-site +1

You'll design, develop, and deploy machine learning models to enhance our Risk and Fraud detection ... What we're looking for: * 5+ years experience in Data Science or ML Engineering * Proficiency in ...

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All JobsRemote Machine Learning Compiler Engineer JobsRemote Machine Learning Compiler Engineer Jobs in Alameda, CA

Remote Machine Learning Compiler Engineer information

See Alameda, CA salary details

$85K

$189.8K

$232.3K

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

As of Jun 19, 2026, the average yearly pay for remote machine learning compiler engineer in Alameda, CA is $189,767.00, according to ZipRecruiter salary data. Most workers in this role earn between $162,100.00 and $232,300.00 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.
What are popular job titles related to Remote Machine Learning Compiler Engineer jobs in Alameda, CA? For Remote Machine Learning Compiler Engineer jobs in Alameda, CA, the most frequently searched job titles are:
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What cities near Alameda, CA are hiring for Remote Machine Learning Compiler Engineer jobs? Cities near Alameda, CA with the most Remote Machine Learning Compiler Engineer job openings:
Remote Machine Learning Compiler Engineer jobs near you
Senior Machine Learning Engineer

Senior Machine Learning Engineer

The Voleon Group

Berkeley, CA • On-site, Remote

$290K - $395K/yr

Full-time

Posted 7 hours ago

Job description

Voleon is a technology company that applies state-of-the-art AI and machine learning techniques to real-world problems in finance. For nearly two decades, we have led our industry and worked at the frontier of applying AI/ML to investment management. We have become a multibillion-dollar asset manager, and we have ambitious goals for the future.
Your colleagues will include internationally recognized experts in artificial intelligence and machine learning research as well as highly experienced finance and technology professionals. In addition to our enriching and collegial working environment, we offer highly competitive compensation and benefits packages, technology talks by our experts, a beautiful modern office, daily catered lunches, and more.
As a Senior Machine Learning Engineer on one of Voleon's Research teams, you will partner directly with research staff to advance our quantitative trading strategies. You will translate novel research ideas into production-quality code, build and maintain the data pipelines and modeling infrastructure that underpin our strategies, and apply your own strong mathematical intuition to solve open-ended technical challenges.
This role lives at the boundary of research and engineering. You will be expected to understand the statistical and mathematical concepts your research partners work with, contribute meaningfully to technical discussions about model design and evaluation, and ensure that the resulting systems are performant, reliable, and maintainable. You will work at the intersection of Computer Science, Mathematics, and Statistics - building high-performance tools that enable world-class research while maintaining a high engineering standard.
Responsibilities
  • Partner with PhD researchers to design, implement, and productize machine learning models that drive quantitative trading strategies
  • Develop and maintain complex data pipelines, including data ingestion, feature engineering, validation, and quality monitoring
  • Translate research prototypes and novel ideas into performant, well-tested, production-ready code
  • Build extensible tools and frameworks that accelerate the model development and experimentation lifecycle
  • Supervise, understand, and remediate subtle data quality issues across both research and production environments
  • Proactively lead projects from requirements through delivery, making autonomous decisions about scope, dependencies, and trade-offs, with an emphasis on long-term maintainability
  • Coordinate and contribute to deployment efforts while guiding junior engineers and researchers; align with research and engineering stakeholders on ownership, execution, and prioritization
  • Foster engineering consistency, standards, and best practices within Research

Requirements
  • Bachelor's degree (or higher) in Computer Science, Applied Mathematics, Statistics, or a related quantitative field
  • 5+ years of professional software engineering experience, with strong CS fundamentals (data structures, algorithms, systems design)
  • Demonstrated mathematical maturity - comfort with the concepts and notation used in statistics, linear algebra, optimization, and probability
  • Deep proficiency in Python; experience with R and/or C/C++ is a strong plus
  • Extensive experience with numerical and data science libraries (e.g., NumPy, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow, or similar)
  • Proven experience building or maintaining machine learning systems in a distributed computing environment
  • Proficiency developing in a Linux environment with attention to performance, correctness, and reproducibility
  • Exceptional attention to detail, particularly when working with imperfect or heterogeneous data
  • Strong verbal and written communication skills, and the ability to collaborate effectively with researchers whose primary expertise is not software engineering

Preferred Qualifications
  • Experience with experiment management, model evaluation pipelines, or ML workflow orchestration
  • Familiarity with modern ML/AI infrastructure patterns (model serving, feature stores, distributed training)
  • Experience with performance profiling and optimization of numerical or modeling code
  • Prior exposure to financial data, time-series analysis, or quantitative research environments

"Friends of Voleon" Candidate Referral Program
If you have a great candidate in mind for this role and would like to have the potential to earn $15,000 if your referred candidate is successfully hired and employed by The Voleon Group, please use this form to submit your referral. For more details regarding eligibility, terms and conditions please make sure to review the Voleon Referral Bonus Program.
Equal Opportunity Employer
The Voleon Group is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.
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About Voleon Group

Sourced by ZipRecruiter

Industry

Investment management and consulting services

Company size

11 - 50 Employees

Headquarters location

Berkeley, CA, US

Year founded

2007

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