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Machine Learning Engineer Jobs in Reston, VA (NOW HIRING)

Machine Learning Engineer

Arlington, VA · On-site

$77K - $176K/yr

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 conduct ...

Machine Learning Engineer

Arlington, VA · On-site

$77K - $176K/yr

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 conduct ...

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA. The ideal candidate will bring hands-on experience in machine learning, advanced analytics, and AI ...

Machine Learning Engineer

Arlington, VA · On-site

$77K - $176K/yr

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 conduct ...

Showing results 21-40

Machine Learning Engineer information

See Reston, VA salary details

$32.8K

$134.2K

$201.7K

How much do machine learning engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for machine learning engineer in Reston, VA is $134,212.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,800.00 and $161,600.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Reston, VA?

The most popular types of Machine Learning Engineer jobs in Reston, VA are:

What are popular job titles related to Machine Learning Engineer jobs in Reston, VA?

For Machine Learning Engineer jobs in Reston, VA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer jobs in Reston, VA look for?

The top searched job categories for Machine Learning Engineer jobs in Reston, VA are:

What cities near Reston, VA are hiring for Machine Learning Engineer jobs?

Cities near Reston, VA with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Reston, VA as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $134,212 per year, or $64.5 per hour.

Machine Learning / Federated-Learning Engineer

Mclean, VA • On-site

Steampunk
IT Services • 201 - 500 employees

$125 - $150/hr

Other

Posted 14 days ago


Job description

Overview

We are seeking a Machine Learning (ML) / Federated-Learning Engineer responsible for developing, implementing, and supporting machine learning solutions within controlled and distributed environments. This role will support the Bounded Use Case B demonstration through controlled model adaptation, fine-tuning, and federated learning workflows.

The ML / Federated-Learning Engineer will work across the machine learning lifecycle to develop and integrate model training and adaptation workflows, support distributed and federated learning capabilities, evaluate model performance, and ensure solutions operate within defined technical and security constraints. This role requires strong hands-on experience with machine learning engineering, model development, and distributed computing environments.

Contributions
  • Design, develop, and implement machine learning solutions supporting the Bounded Use Case B demonstration
  • Develop and execute controlled model adaptation and fine-tuning workflows based on defined use cases and requirements
  • Design, implement, and support federated learning workflows that enable distributed model training and adaptation
  • Develop and maintain machine learning pipelines supporting data preparation, model training, fine-tuning, evaluation, and deployment
  • Analyze and preprocess data, including feature engineering and transformation, to support machine learning workflows
  • Configure and optimize machine learning models and training processes to meet defined performance and operational requirements
  • Evaluate model performance, behavior, and effectiveness using established metrics and validation techniques
  • Develop processes and controls to ensure model adaptation and training occur within defined technical, security, and operational boundaries
  • Integrate machine learning capabilities with existing applications, platforms, data sources, and infrastructure
  • Troubleshoot model training, integration, performance, and distributed learning issues
  • Develop reusable code, tools, and automation to support machine learning and federated learning workflows
  • Collaborate with data scientists, software engineers, cloud engineers, cybersecurity teams, and other technical stakeholders to develop and integrate machine learning capabilities
  • Document machine learning architectures, workflows, configurations, testing results, and technical implementation decisions
  • Support version control, CI/CD, and other software engineering practices throughout the machine learning development lifecycle
  • Support an Agile software development lifecycle
  • Maintain awareness of emerging machine learning, model fine-tuning, federated learning, and distributed AI technologies and practices
Qualifications

Required:

  • Ability to obtain and maintain a government security clearance
  • Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Engineering, Mathematics, or a related technical field, or equivalent relevant experience
  • 5+ years of experience in software engineering, data science, machine learning, AI engineering, or related technical disciplines, including hands-on machine learning engineering experience
  • Hands-on experience developing, training, fine-tuning, and evaluating machine learning models
  • Experience designing and implementing machine learning training and inference workflows
  • Experience with federated learning, distributed machine learning, or distributed model training concepts and architectures
  • Strong programming experience using Python and common machine learning libraries and frameworks
  • Experience with machine learning frameworks such as PyTorch, TensorFlow, scikit-learn, or equivalent technologies
  • Experience with data preprocessing, feature engineering, and model evaluation techniques
  • Experience developing and maintaining data and machine learning pipelines
  • Knowledge of model evaluation techniques, performance metrics, and validation methodologies
  • Experience integrating machine learning models and capabilities into applications or production environments
  • Understanding of distributed computing concepts and architectures
  • Knowledge of cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP)
  • Experience with version control systems such as Git and CI/CD practices
  • Experience troubleshooting machine learning model, pipeline, and integration issues
  • Strong analytical, problem-solving, communication, and collaboration skills

Preferred:

  • Hands-on experience implementing federated learning architectures or workflows
  • Experience with federated learning frameworks or technologies
  • Experience with large language models (LLMs), foundation models, or other generative AI technologies
  • Experience deploying and operating machine learning workloads in cloud environments
  • Knowledge of MLOps practices, model lifecycle management, and automated ML pipelines
  • Experience implementing machine learning solutions within controlled, secure, or restricted environments
  • Experience working within federal government or other highly regulated environments
  • Relevant cloud, machine learning, or AI certification
About steampunk

Steampunk relies on several factors to determine salary, including but not limited to geographic location, contractual requirements, education, knowledge, skills, competencies, and experience. The projected compensation range for this position is $115,000 to $150,000. The estimate displayed represents a typical annual salary range for this position. Annual salary is just one aspect of Steampunk’s total compensation package for employees. Learn more about additional Steampunk benefits here.

Identity Statement

As part of the application process, you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.

Steampunk is a Change Agent in the Federal contracting industry, bringing new thinking to clients in the Homeland, Federal Civilian, Health and DoD sectors. Through our Human-Centered delivery methodology, we are fundamentally changing the expectations our Federal clients have for true shared accountability in solving their toughest mission challenges.If you want to learn more about our story, visit http://www.steampunk.com.

We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.Steampunk participates in the E-Verify program.

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