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Remote Machine Learning Compiler Engineer Jobs in Burien, WA

Meta

Software Engineer, Systems ML

Bellevue, WA · On-site +1

$183K/yr

In this role, you will work at the intersection of machine learning research and systems ... Experience with ML compiler stacks such as MLIR, XLA, TVM, or Triton, and familiarity with hardware ...

Expedia

Machine Learning Scientist III

Seattle, WA · Remote

Our Machine Learning and Data Science team are growing! We are looking to hire researchers and data ... Partner closely with product managers, engineers, and business stakeholders to understand ...

Expedia

Senior Machine Learning Scientist

Seattle, WA · Remote

$104K - $142K/yr

Partners closely with product, engineering, and operations while mentoring junior scientists and ... Our Machine Learning and Data Science team is growing. We are looking for a Senior Machine Learning ...

Axon

Senior Machine Learning Engineer II

Seattle, WA · On-site +1

$118K - $163K/yr

Your Impact We are seeking a seasoned Machine Learning Engineer to join a new team building agentic video and multimodal reasoning systems. As a senior engineer on this team you will own the systems ...

Zortech Solutions

MLOps Engineer

Bellevue, WA · Remote

Bellevue, WA Remote Work100% Primary SkillsAWS Cloud Formation * MLOps Engineer to work on AWS ... Overall, 8-10 years of solid experience in the areas of data engineering / machine learning / data ...

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All JobsMachine Learning Compiler Engineer JobsRemote Machine Learning Compiler Engineer JobsRemote Machine Learning Compiler Engineer Jobs in Burien, WA

Remote Machine Learning Compiler Engineer information

See Burien, WA salary details

$85.8K

$191.5K

$234.4K

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

As of Jul 13, 2026, the average yearly pay for remote machine learning compiler engineer in Burien, WA is $191,489.00, according to ZipRecruiter salary data. Most workers in this role earn between $163,500.00 and $234,400.00 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 the most commonly searched types of Machine Learning Compiler Engineer jobs in Burien, WA? The most popular types of Machine Learning Compiler Engineer jobs in Burien, WA are:
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What cities near Burien, WA are hiring for Remote Machine Learning Compiler Engineer jobs? Cities near Burien, WA with the most Remote Machine Learning Compiler Engineer job openings:
Remote Machine Learning Compiler Engineer jobs near you
Software Engineer, Systems ML

Software Engineer, Systems ML

Meta

Bellevue, WA • On-site, Remote

$183K/yr

Full-time

Posted 27 days ago

Meta rating

7.5

Company rating: 7.5 out of 10

Based on 44 frontline employees who took The Breakroom Quiz

136th of 209 rated software companies

Job description

Meta is seeking a Research Engineer specializing in Systems Machine Learning to help design and build the infrastructure and algorithmic foundations that power large-scale AI systems across Meta's product ecosystem. In this role, you will work at the intersection of machine learning research and systems engineering, developing novel approaches to training efficiency, model serving, distributed computation, and hardware-software co-design. You will collaborate with research scientists and product engineers to translate cutting-edge ML research into production-grade systems that operate at massive scale, directly shaping the performance and reliability of Meta's AI-driven products.
Software Engineer, Systems ML Responsibilities:
  • Design and implement scalable systems for distributed ML training and inference, including optimizations across compute, memory, and communication bottlenecks
  • Develop and evaluate novel techniques for accelerating AI research workflows such as training, inference, RL, evals on latest generation hardware platforms
  • Lead the architecture and end-to-end delivery of major systems ML initiatives, coordinating across research scientists, product engineers, and external partners
  • Establish performance benchmarking frameworks and profiling pipelines to identify bottlenecks and drive measurable improvements in training throughput and inference latency
  • Define service level objectives and reliability standards for ML training and serving systems, building dashboards and runbooks to reduce incident response time
  • Apply AI-assisted development workflows to accelerate implementation, code review, and systems analysis, serving as a model for AI-native engineering practices within the team
  • Collaborate with cross-functional partners in infrastructure, and product engineering to co-design ML systems that maximize research velocity and researcher experience
  • Mentor other engineers on systems ML best practices, distributed training patterns, and debugging methodologies for large-scale ML infrastructure
  • Communicate technical trade-offs, architectural decisions, and experimental results clearly to both engineering and research audiences through design documents and presentations
  • Contribute to the broader research community by publishing findings on systems ML advances at leading venues

Minimum Qualifications:
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 8+ years of experience in systems engineering, machine learning infrastructure, or a closely related field
  • Experience designing and optimizing distributed ML training or inference systems at scale, including proficiency with frameworks such as PyTorch, JAX, or TensorFlow
  • Experience with low-level systems programming in C++ or CUDA, including performance profiling, kernel optimization, or compiler-level ML optimizations
  • Experience leading the technical design and delivery of complex, cross-functional systems ML projects from inception through production deployment
  • Experience using data-driven methods and experimentation to evaluate and validate systems performance improvements

Preferred Qualifications:
  • Master's or PhD degree in Computer Science, Electrical Engineering, Machine Learning, or a related technical field
  • Track record of publishing research on systems ML topics at venues such as MLSys, OSDI, SOSP, NeurIPS, or ICML
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Experience with ML compiler stacks such as MLIR, XLA, TVM, or Triton, and familiarity with hardware-software co-design for AI accelerators
  • Experience building automated tooling or frameworks that improve engineering efficiency across ML infrastructure teams
  • Experience with model parallelism strategies including tensor parallelism, pipeline parallelism, and expert parallelism for large-scale model training

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$183,997/year to $257,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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