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Machine Learning Infrastructure Engineer Jobs in Washington

Quevera LLC

Software Engineer II

Herndon, VA · On-site

$100K - $137K/yr

Working alongside applied scientists and engineering teams, you will design scalable machine learning pipelines, fine-tune Vision-Language Models (VLMs), build AWS-based training infrastructure, and ...

Quevera LLC

Software Engineer II

Herndon, VA · On-site

$100K - $137K/yr

Working alongside applied scientists and engineering teams, you will design scalable machine learning pipelines, fine-tune Vision-Language Models (VLMs), build AWS-based training infrastructure, and ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... ML infrastructure, workflow orchestration, storage, and database services. * Familiarity or ...

System One

Machine Learning/AI Engineer

Merrifield, VA · Remote

... AI infrastructure. Responsibilities • Build and enhance machine learning models through all ... data engineers, data scientists, and data visualization to deliver projects. • Research and ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... ML infrastructure, workflow orchestration, storage, and database services. * Familiarity or ...

System One

Machine Learning/AI Engineer

Merrifield, VA · Remote

... AI infrastructure. Responsibilities • Build and enhance machine learning models through all ... data engineers, data scientists, and data visualization to deliver projects. • Research and ...

System One

Machine Learning/AI Engineer

Merrifield, VA · Remote

... AI infrastructure. Responsibilities • Build and enhance machine learning models through all ... data engineers, data scientists, and data visualization to deliver projects. • Research and ...

Beyond SOF

Engineer, Machine Learning

Washington, DC · On-site

The Machine Learning Engineer is responsible for developing and implementing machine learning models and algorithms to solve complex problems. Main Responsibilities and Duties: Develop and implement ...

Leidos

Infrastructure Engineer

Glen Echo, MD · On-site

$107K - $195K/yr

We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross ... As an Infrastructure Engineer, you will be responsible for technical duties such as infrastructure ...

Leidos

Infrastructure Engineer

Takoma Park, MD · On-site

$107K - $195K/yr

We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross ... As an Infrastructure Engineer, you will be responsible for technical duties such as infrastructure ...

Leidos

Infrastructure Engineer

Bethesda, MD · On-site

$115K - $150K/yr

We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross ... As an Infrastructure Engineer, you will be responsible for technical duties such as infrastructure ...

Leidos

Infrastructure Engineer

Gaithersburg, MD · On-site

$107K - $195K/yr

We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross ... As an Infrastructure Engineer, you will be responsible for technical duties such as infrastructure ...

Somatus, Inc.

Machine Learning Engineer

Mclean, VA · On-site

$105K - $115K/yr

As a Machine Learning Engineer at Somatus, you will work collaboratively with our data and ... Experience with cloud infrastructure (Azure, AWS, or GCP) * Experience with Docker * Experience ...

Leidos

Infrastructure Engineer

Washington, DC · On-site

$107K - $195K/yr

We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross ... As an Infrastructure Engineer, you will be responsible for technical duties such as infrastructure ...

Leidos

Infrastructure Engineer

Bethesda, MD · On-site

$107K - $195K/yr

We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross ... As an Infrastructure Engineer, you will be responsible for technical duties such as infrastructure ...

Leidos

Infrastructure Engineer

Bethesda, MD · On-site

$115K - $150K/yr

We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross ... As an Infrastructure Engineer, you will be responsible for technical duties such as infrastructure ...

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All JobsMachine Learning Infrastructure Engineer JobsMachine Learning Infrastructure Engineer Jobs in Washington

Machine Learning Infrastructure Engineer information

What are some common challenges faced by Machine Learning Infrastructure Engineers, and how can these be addressed on the job?

Machine Learning Infrastructure Engineers often face challenges such as ensuring infrastructure scalability, managing resource allocation, and maintaining system reliability while supporting rapid experimentation by data science teams. Balancing the needs for flexibility in research environments with production-grade stability requires a deep understanding of both engineering best practices and the unique requirements of machine learning workflows. Collaboration with data scientists, clear communication about infrastructure capabilities, and staying current with fast-evolving technologies are key strategies for success. Most companies encourage ongoing learning and provide opportunities to contribute to architecture decisions, which makes this a rewarding environment for problem-solvers and innovators.

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

To thrive as a Machine Learning Infrastructure Engineer, you need a strong background in computer science, cloud computing, distributed systems, and experience with machine learning frameworks, often supported by a degree in a related field. Familiarity with tools such as Docker, Kubernetes, Terraform, as well as cloud platforms like AWS, GCP, or Azure, and certifications in cloud or DevOps technologies are highly valued. Strong problem-solving abilities, effective communication, and collaboration skills help engineers work seamlessly with data scientists and cross-functional teams. These skills are essential to design, implement, and maintain robust, scalable infrastructure that enables efficient machine learning development and deployment.

What is a Machine Learning Infrastructure Engineer job?

A Machine Learning Infrastructure Engineer designs, builds, and maintains the systems that support the development and deployment of machine learning models. This includes managing data pipelines, optimizing model training and inference, and ensuring scalability and reliability in production environments. They work closely with data scientists, ML engineers, and DevOps teams to create efficient workflows and infrastructure. Key technologies often include cloud platforms, containerization, orchestration tools, and distributed computing frameworks.

What are popular job titles related to Machine Learning Infrastructure Engineer jobs in Washington? For Machine Learning Infrastructure Engineer jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Machine Learning Infrastructure Engineer jobs in Washington look for? The top searched job categories for Machine Learning Infrastructure Engineer jobs in Washington are:
What cities in Washington are hiring for Machine Learning Infrastructure Engineer jobs? Cities in Washington with the most Machine Learning Infrastructure Engineer job openings:
Machine Learning Infrastructure Engineer jobs near you
Infographic showing various Machine Learning Infrastructure Engineer job openings in Washington as of July 2026, with employment types broken down into 90% Full Time, 8% Part Time, and 2% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

Dark Wolf Solutions

Chantilly, VA

Full-time

Re-posted 2 days ago

Job description

Dark Wolf constructs and deploys data management and analytics solutions for the defense and intelligence communities. We're proud to boast a world-class engineering team that thrives on rolling up their sleeves to solve your mission's biggest challenges.

Dark Wolf is seeking a highly motivated and self-directed professional to fill the role of Machine Learning (ML) Engineer to support our team in Northern Virginia.

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:

  • 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, clusting, 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 Skills:

  • 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.

Position Clearance Requirement:

TS/SCI with Full-Scope Polygraph

This position is located in Chantilly/Herndon, VA.

We are proud to be an EEO/AA employer Minorities/Women/Veterans/Disabled and other protected categories.
In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.