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Junior Machine Learning Compiler Engineer Jobs (NOW HIRING)

Nvidia

Senior ML Compiler Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

Innovate and develop new machine learning compiler and systems technologies * Design, implement ... Collaborate closely with other engineering teams at NVIDIA to build high impact solutions for ...

Nvidia

OR · On-site

$104K - $143K/yr

Innovate and develop new machine learning compiler and systems technologies * Design, implement ... Collaborate closely with other engineering teams at NVIDIA to build high impact solutions for ...

Nvidia

Senior ML Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

Innovate and develop new machine learning compiler and systems technologies * Design, implement ... Collaborate closely with other engineering teams at NVIDIA to build high impact solutions for ...

Nvidia

Senior ML Compiler Engineer

Austin, TX · On-site

$103K - $142K/yr

Innovate and develop new machine learning compiler and systems technologies * Design, implement ... Collaborate closely with other engineering teams at NVIDIA to build high impact solutions for ...

NVIDIA

Senior Compiler Engineer - AI

Santa Clara, CA · On-site

$122K - $168K/yr

The role involves driving innovative solutions in compilers and developer tools through applied machine learning and AI, focusing on building AI-driven compiler intelligence for production pipelines.

NVIDIA

Senior Compiler Engineer - AI

Austin, TX · On-site

$103K - $142K/yr

The role involves driving innovative solutions in compilers and developer tools through applied machine learning and AI, focusing on building AI-driven compiler intelligence for production pipelines.

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Junior Machine Learning Compiler Engineer information

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$33.5K

$71.8K

$109.5K

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

As of Jul 5, 2026, the average yearly pay for junior machine learning compiler engineer in the United States is $71,799.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,500.00 and $80,000.00 per year, depending on experience, location, and employer.

What are typical projects and responsibilities for a Junior Machine Learning Compiler Engineer in a collaborative team setting?

As a Junior Machine Learning Compiler Engineer, you can expect to work on projects that focus on optimizing machine learning models for performance and deployment across various hardware platforms. Typical responsibilities include assisting in developing and debugging compiler passes, implementing optimizations, and contributing to code reviews. You'll frequently collaborate with senior engineers, data scientists, and hardware specialists to ensure that models are efficiently translated and executed. This role offers valuable learning opportunities through hands-on coding, exposure to state-of-the-art ML frameworks, and regular team meetings for knowledge sharing and mentorship.

What does a Junior Machine Learning Compiler Engineer do?

A Junior Machine Learning Compiler Engineer helps design, develop, and optimize compilers for machine learning models. Their work involves translating high-level machine learning code into efficient low-level code that can run on various hardware platforms, such as CPUs, GPUs, or specialized AI chips. They often collaborate with software engineers and data scientists to ensure that machine learning workloads run efficiently and correctly. This role typically involves programming, debugging, and performance tuning, often using languages like C++, Python, and specialized frameworks.

What are the key skills and qualifications needed to thrive as a Junior Machine Learning Compiler Engineer, and why are they important?

To thrive as a Junior Machine Learning Compiler Engineer, you need a solid background in computer science fundamentals, programming (especially C++ and Python), and foundational knowledge of machine learning and compiler theory. Familiarity with frameworks and tools such as LLVM, TensorFlow, MLIR, and version control systems is typically required, along with a relevant bachelor’s or master’s degree. Strong problem-solving abilities, attention to detail, and effective teamwork and communication skills set standout candidates apart. These skills and qualities are crucial for efficiently optimizing machine learning models for various hardware targets and collaborating on innovative compiler solutions.

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

AspectJunior Machine Learning Compiler EngineerData Scientist
Required CredentialsBachelor's in Computer Science, Software Engineering, or related field; knowledge of compiler design and ML frameworksBachelor's or higher in Data Science, Statistics, Computer Science, or related field; strong analytical skills
Work EnvironmentSoftware development teams, focusing on compiler optimization for ML modelsData analysis teams, focusing on data interpretation and model development
Employer & Industry UsageTech companies, AI startups, hardware firmsTech firms, finance, healthcare, research institutions

The Junior Machine Learning Compiler Engineer primarily focuses on developing and optimizing compilers for machine learning models, requiring programming and compiler knowledge. In contrast, a Data Scientist analyzes data, builds models, and provides insights. Both roles are essential in AI and tech industries but differ in technical focus and daily tasks.

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Junior Machine Learning Compiler Engineer jobs near you
Infographic showing various Junior Machine Learning Compiler Engineer job openings in the United States as of June 2026, with employment types broken down into 85% Full Time, 3% Part Time, 8% Contract, and 4% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $71,799 per year, or $34.5 per hour.
Compiler Engineer

Compiler Engineer

TetraMem - Accelerate The World

San Jose, CA

$160K - $300K/yr

Other

Posted 22 days 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.

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