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Remote Machine Learning Compiler Engineer Jobs in Washington, DC

Capital One

Sr. Lead Machine Learning Engineer (IC)

Mclean, VA · On-site +1

$103K - $136K/yr

Sr. Lead Machine Learning Engineer (IC) 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 ...

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All JobsMachine Learning Compiler Engineer JobsRemote Machine Learning Compiler Engineer JobsRemote Machine Learning Compiler Engineer Jobs in Washington, DC

Remote Machine Learning Compiler Engineer information

See Washington, DC salary details

$84.9K

$189.6K

$232.2K

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

As of Aug 19, 2026, the average yearly pay for remote machine learning compiler engineer in Washington, DC is $189,639.00, according to ZipRecruiter salary data. Most workers in this role earn between $162,000.00 and $232,200.00 per year, depending on experience, location, and employer.

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.

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 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 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 most commonly searched types of Machine Learning Compiler Engineer jobs in Washington, DC?

The most popular types of Machine Learning Compiler Engineer jobs in Washington, DC are:

What are popular job titles related to Remote Machine Learning Compiler Engineer jobs in Washington, DC?

For Remote Machine Learning Compiler Engineer jobs in Washington, DC, the most frequently searched job titles are:

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The top searched job categories for Remote Machine Learning Compiler Engineer jobs in Washington, DC are:

Remote Machine Learning Compiler Engineer jobs near you

Senior Machine Learning Engineer

AHU Technologies Inc

Washington, DC • Remote

$150K - $300K/yr

Full-time

Posted 21 days ago

Job description

Location: United States - remote
Visa: US Citizens or Green Card Holders
Fluency in Chinese/Mandarin is required, so only reach out exclusively to candidates of Chinese ethnic background.
What you will own
  • Build recommendation and search across feed, discovery, search, and content continuation.
  • Own retrieval/ranking: candidate generation, embeddings, two-tower models, features, and serving quality.
  • Design, launch, and analyze recommendation/search experiments.
Requirements
  • 5+ years industry experience building production ML systems with senior ownership.
  • Bachelor's degree from a recognized university in China is required 
  • Hands-on recommendation, search, ranking, ads ranking, feed ranking, or content discovery systems.
  • Consumer apps, entertainment, social, gaming, creator, or engagement-driven products.
  • Two-tower models, embedding retrieval, candidate generation, ranking, and online/offline evaluation.
Hard filters
  • 5+ years industry experience building production ML systems with senior ownership.
  • Hands-on recommendation, search, ranking, ads ranking, feed ranking, or content discovery systems.
  • Consumer apps, entertainment, social, gaming, creator, or engagement-driven products.
  • Two-tower models, embedding retrieval, candidate generation, ranking, and online/offline evaluation.
Strong fit
  • Build recommendation and search across feed, discovery, search, and content continuation.
  • Own retrieval/ranking: candidate generation, embeddings, two-tower models, features, and serving quality.
  • Background in the entertainment or social media industry (e.g., TikTok, Pinterest, Instagram). 
  • Design, launch, and analyze recommendation/search experiments.
Bonus:
  • Bonus signal: 5+ years production ML
  • Bonus signal: recommendation systems
  • Bonus signal: search ranking
  • Bonus signal: embedding retrieval
Anti-signals
  • Cannot show core Senior Machine Learning Engineer, Recommendation experience
  • Not comfortable with the listed work mode
  • Low ownership, coordination-only, or no shipped examples

This is a remote position.