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From Home Machine Learning Compiler Engineer Jobs

Senior Compiler Engineer

San Jose, CA · On-site

$160K - $210K/yr

Work with various machine-learning frameworks to compile models to our custom hardware. * Debug and ... We offer a competitive salary for this role, generally ranging from $160,000 to $210,000, along ...

Senior Compiler Engineer - AI

Austin, TX · On-site

$121K - $160K/yr

The ideal candidate brings broad experience across machine learning, including reinforcement ... Design and implement end-to-end compiler optimization workflows, from feature engineering and model ...

CI Infrastructure Engineer

Raleigh, NC · On-site

$76K - $102K/yr

... supports our Machine Learning compiler stack. In this role, you will ensure the reliability ... at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to ...

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 ... What we expect from one another is simple and clear: Initiative, Collaboration, and Completion. We ...

The ideal candidate brings broad experience across machine learning, including reinforcement ... Design and implement end-to-end compiler optimization workflows, from feature engineering and model ...

Senior Compiler Engineer - AI

Austin, TX

$121K - $160K/yr

The ideal candidate brings broad experience across machine learning, including reinforcement ... Design and implement end-to-end compiler optimization workflows, from feature engineering and model ...

Senior Compiler Engineer - AI

Redmond, WA

$137K - $180K/yr

The ideal candidate brings broad experience across machine learning, including reinforcement ... Design and implement end-to-end compiler optimization workflows, from feature engineering and model ...

The Principal Compiler Engineer - ML Systems will drive innovation in compiler infrastructure and ... Preferred : • Experience with MLIR. • Familiarity with machine learning models and frameworks ...

Showing results 41-60

From Home Machine Learning Compiler Engineer information

See salary details

$31.5K

$128.8K

$193.5K

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

As of Aug 12, 2026, the average yearly pay for from home machine learning compiler engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

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

AspectFrom Home Machine Learning Compiler EngineerFrom Home Data Scientist
Required SkillsProgramming (C++, Python), compiler design, ML frameworksStatistics, data analysis, programming (Python, R), visualization
Work EnvironmentRemote, software development teams, tech companiesRemote, analytics teams, research institutions
Industry UsageTech, AI, hardware optimizationTech, finance, healthcare, research

While both roles often work remotely and require programming skills, the Machine Learning Compiler Engineer focuses on developing and optimizing compilers for ML models, whereas the Data Scientist analyzes data to generate insights. They serve different functions within tech and research industries but may collaborate on AI projects.

More about From Home Machine Learning Compiler Engineer jobs
What cities are hiring for From Home Machine Learning Compiler Engineer jobs? Cities with the most From Home Machine Learning Compiler Engineer job openings:
What are the most commonly searched types of Machine Learning Compiler Engineer jobs? The most popular types of Machine Learning Compiler Engineer jobs are:
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Infographic showing various From Home Machine Learning Compiler Engineer job openings in the United States as of August 2026, with employment types broken down into 2% As Needed, 70% Full Time, 24% Part Time, and 4% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

$160K - $300K/yr

Full-time

Re-posted 6 hours ago


Job description

Responsibilities:

  • Design, develop, and maintain compiler toolchains that translate machine learning models from industry-standard frameworks into optimized workloads for TetraMems analog in-memory computing hardware.

  • Develop runtime systems, software libraries, and SDK components that enable efficient deployment, execution, and management of AI applications on TetraMem accelerators.

  • Implement compiler optimizations, including graph transformations, operator fusion, memory optimization, scheduling, and code generation to maximize performance and energy efficiency.

  • Research and develop innovative techniques to improve machine learning inference speed, latency, throughput, and power consumption across a wide range of AI workloads.

  • Collaborate closely with machine learning engineers to support model conversion, validation, optimization, benchmarking, and deployment.

  • Partner with hardware architects and silicon engineering teams to co-design software and hardware features that improve system performance, programmability, and usability.

  • Develop performance analysis, profiling, debugging, and benchmarking tools to evaluate and optimize AI workloads on current and future TetraMem platforms.

  • Integrate and support industry-standard machine learning frameworks and model formats, including PyTorch, TensorFlow, ONNX, and other emerging AI ecosystems.

  • Lead technical design reviews, contribute to software architecture decisions, and establish best practices for scalable, maintainable, and high-quality software development.

  • Mentor junior engineers, contribute to technical documentation, and help define the long-term roadmap for TetraMems compiler, runtime, and SDK technologies.

Requirements:

  • MS or PhD in Computer Engineering/CS/EE
  • 5+ years industry experience as a compiler engineer or developer
  • Experience developing compilers for GPU, dataflow compilers, or ML compilers
  • Startup mindset/experience

Experience in one or more of the following areas considered a strong plus:

  • Experience in RISC-V CPU/VPU kernel development and optimization
  • Experience providing technical leadership and/or guidance to other engineers
  • Knowledge of popular CPU/GPU compilers such as GCC, Clang
  • Knowledge of ML compilers such as MLIR
  • Experience with LLVM and other open-source compiler libraries and tools
  • Publications on compilation of ML or dataflow programs for HW acceleration

Salary Range: $160,000 - $300,000 / year

TetraMem celebrates diversity and is committed to creating an inclusive environment for all employees. We are proud to be an Equal Opportunity Employer and welcome applicants from all backgrounds. Qualified candidates will receive consideration for employment without regard to race, color, religion, creed, sex, gender identity or expression, sexual orientation, national origin, ancestry, age, marital status, medical condition, disability, genetic information, military or veteran status, or any other characteristic protected by applicable federal, state, or local law.
TetraMem is committed to providing reasonable accommodations to qualified applicants with disabilities throughout the recruitment process. Applicants requiring accommodation may contact Human Resources for assistance.
To ensure a fair, consistent, and efficient hiring process, all candidates must apply through TetraMems official ClearCompany Applicant Tracking System (ATS). Applications submitted through the ATS allow our hiring team to evaluate candidates using a standardized process and ensure timely communication throughout the recruitment process. To promote equal consideration for all applicants, applications submitted outside of the ClearCompany ATS, including direct emails, LinkedIn messages, or unsolicited submissions to employees, may not be reviewed or considered.
We encourage all interested candidates to apply through the official TetraMem Careers page.