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Machine Learning Compiler Engineer Jobs in Virginia

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Machine Learning Engineer

Reston, VA

Machine Learning Engineer Location: Fort Meade, MD Required Clearance : TS/SCI w/ Full-Scope Poly Salary: Competitive We are seeking a highly skilled and motivated Machine Learning Engineer to join ...

Cymertek

Machine Learning Engineer

Tysons, VA · On-site

Machine Learning Engineer LOCATION Tysons, VA 22182 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

Cymertek

Machine Learning Engineer

Chantilly, VA

Machine Learning Engineer LOCATIONChantilly, VA 20151 CLEARANCETS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARYWe are seeking a talented and innovative Machine ...

Cymertek

Machine Learning Engineer

Tysons, VA

Machine Learning Engineer LOCATIONTysons, VA 22182 CLEARANCETS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARYWe are seeking a talented and innovative Machine ...

Cymertek

Machine Learning Engineer

Reston, VA · On-site

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

Cymertek

Machine Learning Engineer

Reston, VA

Machine Learning Engineer LOCATIONReston, VA 20190 CLEARANCETS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARYWe are seeking a talented and innovative Machine ...

Cymertek

Machine Learning Engineer

Chantilly, VA · On-site

Machine Learning Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative ...

Booz Allen Hamilton

Machine Learning Engineer

Arlington, VA · On-site

$77K - $176K/yr

R0242757 Machine Learning Engineer The Opportunity: As an experienced AI and ML engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to ...

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All JobsMachine Learning Compiler Engineer JobsMachine Learning Compiler Engineer Jobs in Virginia

Machine Learning Compiler Engineer information

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$31.2K

$127.7K

$191.8K

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

As of Jun 28, 2026, the average yearly pay for machine learning compiler engineer in Virginia is $127,665.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,600.00 and $153,700.00 per year, depending on experience, location, and employer.

What is a Machine Learning Compiler Engineer job?

A Machine Learning Compiler Engineer focuses on optimizing and building compilers that translate high-level machine learning models into efficient code runnable on specialized hardware (e.g., GPUs, TPUs). They work on improving performance, memory usage, and execution efficiency of ML workloads by designing compiler optimizations, code generation techniques, and leveraging frameworks like LLVM or MLIR. Their role bridges the gap between ML researchers and hardware engineers, ensuring models run efficiently on target platforms.

What are the typical daily responsibilities of a Machine Learning Compiler Engineer?

As a Machine Learning Compiler Engineer, your daily responsibilities often include designing and implementing new compiler optimizations, collaborating with machine learning researchers to support model deployment, and debugging performance or correctness issues in compiled code. You may participate in code reviews, write technical documentation, and conduct benchmarking to evaluate how machine learning models perform on various hardware backends. Close collaboration with hardware engineers, software architects, and data scientists is common, ensuring end-to-end solutions meet both research and production requirements. Staying updated with the latest advancements in both compiler technology and machine learning frameworks is also a key aspect of the role.

What are the key skills and qualifications needed to thrive in the Machine Learning Compiler Engineer position, and why are they important?

A Machine Learning Compiler Engineer needs a deep understanding of computer science fundamentals, compiler theory, and experience with machine learning frameworks, often supported by a relevant degree in computer science or engineering. Proficiency with tools such as LLVM, TVM, MLIR, and languages like C++, Python, and CUDA is typically required, and familiarity with hardware architectures is a plus. Strong problem-solving, teamwork, and communication skills are essential for collaborating with cross-functional teams and addressing complex system issues. These capabilities are important for designing and optimizing compilers that enable scalable and efficient deployment of machine learning models on diverse hardware platforms.

What are the most commonly searched types of Machine Learning Compiler Engineer jobs in Virginia? The most popular types of Machine Learning Compiler Engineer jobs in Virginia are:
What are popular job titles related to Machine Learning Compiler Engineer jobs in Virginia? For Machine Learning Compiler Engineer jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Machine Learning Compiler Engineer jobs in Virginia look for? The top searched job categories for Machine Learning Compiler Engineer jobs in Virginia are:
Machine Learning Compiler Engineer jobs near you

Machine Learning Engineer

Full Scope

Reston, VA

Other

Posted 13 days ago

Job description

Job Title:Machine Learning Engineer
Location:Fort Meade, MD
Required Clearance: TS/SCI w/ Full-Scope Poly
Salary:Competitive
We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team. The ideal candidate will have a strong background in machine learning, data science, and software engineering. You will work closely with data scientists, engineers, and product managers to design, develop, and deploy machine learning models and solutions that drive business value.
Key Responsibilities:
  • Design, develop, and implement machine learning models and algorithms to solve real-world problems.
  • Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
  • Conduct data analysis and preprocessing to ensure high-quality data for model training.
  • Optimize and fine-tune models for performance, accuracy, and scalability.
  • Deploy machine learning models into production and monitor their performance.
  • Develop and maintain machine learning pipelines and infrastructure.
  • Stay current with the latest research and advancements in machine learning and AI.
  • Participate in code reviews, team meetings, and contribute to a collaborative development environment.
  • Document processes, models, and findings comprehensively.
Qualifications:
  • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field. Ph.D. is a plus.
  • Proven experience as a Machine Learning Engineer or in a similar role.
  • Strong proficiency in programming languages such as Python, R, or Java.
  • Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
  • Solid understanding of machine learning algorithms, including supervised and unsupervised learning, reinforcement learning, and deep learning.
  • Experience with data processing tools like Pandas, NumPy, and data visualization tools such as Matplotlib or Seaborn.
  • Familiarity with cloud platforms like AWS, Google Cloud, or Azure for model deployment and scaling.
  • Strong problem-solving skills and the ability to think critically and analytically.
  • Excellent communication and teamwork skills.
Preferred Qualifications:
  • Experience with natural language processing (NLP) and computer vision.
  • Familiarity with big data technologies such as Hadoop, Spark, or Kafka.
  • Knowledge of software development best practices and version control systems like Git.
  • Experience with containerization tools like Docker and orchestration tools like Kubernetes.
  • Previous experience in a fast-paced, startup environment.

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