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Machine Learning Compiler Engineer Jobs in Virginia

They are seeking a highly motivated Machine Learning Engineer to design, develop, and implement machine learning models and algorithms to solve specific business problems. Responsibilities : • ...

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 ...

They are seeking a highly motivated Machine Learning Engineer to design, develop, and implement machine learning models and algorithms to solve business problems. Responsibilities : • Design ...

Machine Learning Engineer

Mclean, VA · On-site +1

$115K - $150K/yr

We are looking for a more than just a "Machine Learning Engineer", but a technologist with excellent communication and customer service skills and a passion for data and problem solving.

Machine Learning Engineer - AI Data Trainer Location: Remote About The Job At Alignerr, we partner with the world's leading AI research teams and labs to build and train cutting‐edge AI models.

New

Machine Learning Engineer

Mclean, VA · On-site

$115K - $150K/yr

We are looking for a more than just a "Machine Learning Engineer", but a technologist with excellent communication and customer service skills and a passion for data and problem solving.

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 ...

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 ...

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 ...

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 ...

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 ...

SW Engineer Schedule: Full-Time Shift: Day Job Travel: Yes - 10% of the time Minimum Clearance ... The Machine Learning Developer will collaborate with software engineers to create innovative ML/AI ...

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Machine Learning Compiler Engineer information

See Virginia salary details

$31.2K

$127.7K

$191.8K

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

As of Jun 5, 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 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 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 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 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:
Infographic showing various Machine Learning Compiler Engineer job openings in Virginia as of May 2026, with employment types broken down into 94% Full Time, 2% Part Time, 2% Contract, and 2% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $127,665 per year, or $61.4 per hour.

Machine Learning Engineer

Dark Wolf

Herndon, VA • On-site

Full-time

Posted 21 days ago


Job description

Job Summary:
Dark Wolf constructs and deploys data management and analytics solutions for the defense and intelligence communities. They are seeking a highly motivated Machine Learning Engineer to design, develop, and implement machine learning models and algorithms to solve specific business problems.
Responsibilities:
• Design, develop, and implement machine learning models and algorithms to solve specific business problems.
• Build and maintain scalable and robust machine learning pipelines for data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.
• Transform machine learning models into deployable APIs and integrate them with existing applications and infrastructure.
• Collaborate closely with data scientists, software engineers, and product managers to understand requirements and translate them into practical ML solutions.
• Experiment with different machine learning techniques and algorithms to identify the most effective approaches for given problems.
• Evaluate model performance using appropriate metrics and iterate on models to improve accuracy, efficiency, and scalability.
• Monitor and maintain deployed models, ensuring their reliability and performance in production environments.
• Troubleshoot and resolve issues related to machine learning models and pipelines.
• Stay up-to-date with the latest advancements in machine learning, deep learning, and related fields.
• Contribute to the development of best practices and standards for machine learning development and deployment within the team.
• Document machine learning models, experiments, and deployment processes.
• Potentially work with large datasets and big data technologies.
• Optimize machine learning models for performance and efficiency.
Qualifications:
Required:
• Master’s in computer science, Machine Learning, or higher level degree is preferred with of 3+ years of related industry experience in Machine Learning, Computer Science, Data Science or related fields.
• Demonstrated hands-on experience in developing and deploying machine learning models in a production environment.
• Strong programming skills in Python and experience with relevant machine learning libraries and frameworks such as TensorFlow, Keras, PyTorch, scikit-learn, etc.
• Solid understanding of machine learning algorithms (e.g., regression, classification, clustering, dimensionality reduction, deep learning architectures).
• Experience with data preprocessing, feature engineering, and data visualization techniques.
• Familiarity with data storage and processing technologies (e.g., SQL, NoSQL databases, Spark, Hadoop).
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and their machine learning services.
• Understanding of software development principles, version control (e.g., Git), and CI/CD pipelines.
• Strong analytical and problem-solving skills with the ability to interpret data and draw meaningful conclusions.
• Excellent communication and collaboration skills to effectively communicate technical concepts to both technical and non-technical audiences.
Preferred:
• Experience with specific areas of machine learning such as Natural Language Processing (NLP), Computer Vision, or Recommender Systems.
• Experience with MLOps practices and tools for automating and monitoring machine learning workflows.
• Knowledge of containerization technologies like Docker and orchestration tools like Kubernetes.
• Experience with building and deploying RESTful APIs.
• Familiarity with big data technologies and distributed computing.
• Experience with statistical modeling and inference.
Company:
Dark Wolf provides DevSecOps agile software development, information operations, penetration testing and incident response, applied research and rapid prototyping, machine learning, and mission support and engineering services to the Intelligence Community, national security, and Fortune 500 customers. Founded in 2009, the company is headquartered in Herndon, USA, with a team of 501-1000 employees. The company is currently Late Stage.