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Machine Learning Manager Jobs in Virginia (NOW HIRING)

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Machine Learning Engineer

Reston, VA

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:

1872 Consulting

Machine Learning Engineer

Reston, VA · On-site

Working knowledge of machine learning frameworks and the data and computation management mechanisms that surround them in a cloud environment (AWS) * Experience designing, implementing, and ...

Samprasoft

Machine Learning Engineer

Mclean, VA · On-site

... lake, data management, governance and the integration of structured and unstructured data to ... machine learning frameworks such as TensorFlow, XGBoost, scikit-learn, Pytorch and ONNX and ...

ManTech

Machine Learning Engineer

Herndon, VA · On-site

Implement the full MLOps lifecycle to deploy, operationalize, scale, and manage automated machine learning models and analytical solutions. * Develop and test ML applications according to ...

Steampunk

Machine Learning Engineer

Mclean, VA

$115K - $150K/yr

We are looking for seasoned Machine Learning Engineer to work with our existing team of Data ... Ability to manage multiple tasks and projects simultaneously while meeting deadlines. Steampunk ...

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How much do machine learning manager jobs pay per year?

As of May 28, 2026, the average yearly pay for machine learning manager in Virginia is $81,008.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,400.00 and $91,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Manager, and why are they important?

To thrive as a Machine Learning Manager, you need a robust background in machine learning algorithms, statistical analysis, and software engineering, typically supported by an advanced degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and project management platforms, along with experience in deploying ML systems, is essential. Strong leadership, communication, and strategic thinking skills set exceptional managers apart, enabling them to guide teams and align projects with business objectives. These skills are crucial to successfully leading technical teams, ensuring project delivery, and translating complex ML solutions into organizational value.

What are some of the main challenges a Machine Learning Manager faces when leading a team?

A Machine Learning Manager often navigates challenges such as balancing project deadlines with the need for thorough experimentation and research, ensuring clear communication between technical and non-technical stakeholders, and fostering collaboration among data scientists, engineers, and product teams. Additionally, managers must keep their team's skills current with rapidly evolving technologies while also addressing issues like data quality and model deployment in production environments. Successfully overcoming these challenges requires strong leadership, adaptability, and a deep understanding of both business objectives and technical intricacies.

What are Machine Learning Managers?

Machine Learning Managers are professionals responsible for leading teams that develop, implement, and maintain machine learning models and systems. They oversee data scientists, engineers, and other specialists, ensuring projects align with business goals and are delivered on time. Their role often involves coordinating cross-functional teams, managing project timelines, and staying current with the latest advancements in artificial intelligence and machine learning. Additionally, they may be involved in hiring, mentoring, and providing technical guidance to their team.
What are the most commonly searched types of Machine Learning jobs in Virginia? The most popular types of Machine Learning jobs in Virginia are:
What are popular job titles related to Machine Learning Manager jobs in Virginia? For Machine Learning Manager jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Machine Learning Manager jobs in Virginia look for? The top searched job categories for Machine Learning Manager jobs in Virginia are:
What cities in Virginia are hiring for Machine Learning Manager jobs? Cities in Virginia with the most Machine Learning Manager job openings:
Machine Learning Manager jobs near you
Infographic showing various Machine Learning Manager job openings in Virginia as of May 2026, with employment types broken down into 76% Full Time, 17% Part Time, and 7% Contract. Highlights an 59% Physical, 4% Hybrid, and 37% Remote job distribution, with an average salary of $81,008 per year, or $38.9 per hour.
Machine Learning Engineer

Machine Learning Engineer

Dark Wolf Solutions

Herndon, VA • On-site

Other

This job post has expired 1 day ago. Applications are no longer accepted.

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.

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