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Machine Learning Scientist Jobs in Virginia (NOW HIRING)

Venturegloballng

Engineer, Machine Learning

Arlington, VA · On-site

$157K - $185K/yr

Work with data scientists, data engineers, and business analysts to translate business requirements into machine learning solutions. * Build software solutions that are maintainable, scalable and ...

Cymertek

Machine Learning Engineer

Tysons, VA · On-site

Machine Learning Engineer LOCATION Tysons, VA 22182 CLEARANCE TS/SCI Full Poly (Please note this ... You will collaborate with data scientists, engineers, and product teams to turn data into ...

Cymertek

Machine Learning Engineer

Reston, VA · On-site

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this ... You will collaborate with data scientists, engineers, and product teams to turn data into ...

Cymertek

Machine Learning Engineer

Chantilly, VA · On-site

Machine Learning Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this ... You will collaborate with data scientists, engineers, and product teams to turn data into ...

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All JobsMachine Learning Scientist JobsMachine Learning Scientist Jobs in Virginia

Machine Learning Scientist information

See Virginia salary details

$76.3K

$138.5K

$194K

How much do machine learning scientist jobs pay per year?

As of Sep 15, 2026, the average yearly pay for machine learning scientist in Virginia is $138,506.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,107.00 and $154,146.00 per year, depending on experience, location, and employer.

What is a machine learning scientist?

A Machine Learning Scientist researches, develops, and applies machine learning models to solve complex problems. They work on designing algorithms, improving model performance, and analyzing large datasets to extract valuable insights. Their role often involves experimenting with new techniques, optimizing existing models, and collaborating with engineers and data scientists to deploy solutions. Machine Learning Scientists typically have expertise in statistics, mathematics, and programming languages like Python. They work in industries such as healthcare, finance, and technology to drive innovation using artificial intelligence.

What does a machine learning scientist do?

A typical day for a Machine Learning Scientist involves collecting and analyzing large datasets, designing and training machine learning models, and evaluating model performance to ensure accuracy and reliability. You'll often collaborate with data engineers, software developers, and domain experts to define project goals, prepare data, and integrate solutions into production systems. Regular team meetings, code reviews, and brainstorming sessions are common, fostering an environment of shared learning and problem-solving. This collaborative structure not only enhances project outcomes but also offers valuable opportunities for continuous professional growth and skill development.

What skills and qualifications are needed to be a machine learning scientist?

To thrive as a Machine Learning Scientist, you need strong skills in mathematics, statistics, programming (typically in Python or R), and a graduate degree in computer science, data science, or a related field. Expertise in machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), proficiency with data processing tools, and experience with cloud platforms (like AWS or GCP) are commonly required; certifications in these can be advantageous. Critical thinking, problem-solving, and effective communication are important soft skills for collaborating with cross-functional teams and conveying complex concepts. These abilities enable Machine Learning Scientists to build effective models, deliver actionable insights, and drive innovation within organizations.

Is machine learning a high paying job?

Machine Learning Scientists typically earn high salaries due to the specialized skills required, such as programming, statistical analysis, and experience with tools like Python and TensorFlow. Salaries vary by industry, experience, and location but are generally above average compared to many other tech roles.

What are the most commonly searched types of Machine Learning Scientist jobs in Virginia?

The most popular types of Machine Learning Scientist jobs in Virginia are:

What are popular job titles related to Machine Learning Scientist jobs in Virginia?

For Machine Learning Scientist jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Machine Learning Scientist jobs in Virginia look for?

The top searched job categories for Machine Learning Scientist jobs in Virginia are:

Machine Learning Scientist jobs near you
Infographic showing various Machine Learning Scientist job openings in Virginia as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 73% Full Time, 21% Part Time, 3% Contract, and 1% Nights. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution, with an average salary of $138,506 per year, or $66.6 per hour.

Data Scientist / Machine Learning Engineer

Arlington, VA • On-site

ECS
See more jobs at ECSexternal

$160K - $185K/yr

Full-time

Posted 10 days ago

Job description

Everforth ECS is seeking a Data Scientist/Machine Learning Engineer to join our team in Arlington, VA (Hybrid). This position is contingent upon award.
We are seeking a talented Data Scientist / Machine Learning Engineer to design, develop, deploy, and optimize advanced analytics and machine learning solutions that drive business insights and operational efficiencies. This role combines data science, machine learning engineering, and software development to transform complex data into scalable, production-ready AI and predictive analytics solutions.
The ideal candidate will possess expertise in statistical analysis, machine learning algorithms, AI/ML-assisted clustering, feature engineering, model deployment, anomaly detection, and cloud-based AI platforms while collaborating closely with business stakeholders, data engineers, and technology teams.
Key Responsibilities
Data Science & Advanced Analytics
  • Analyze structured and unstructured data to identify trends, patterns, and actionable insights.
  • Develop predictive, prescriptive, and classification models to support business objectives.
  • Perform exploratory data analysis (EDA), feature engineering, and statistical modeling.
  • Design experiments and evaluate model performance using appropriate statistical methodologies.
  • Present findings and recommendations to technical and non-technical stakeholders.
  • Support efforts in anomaly detection.

Machine Learning Development
  • Design, build, train, and optimize machine learning and deep learning models.
  • Develop solutions for forecasting, anomaly detection, natural language processing (NLP), recommendation systems, and computer vision applications.
  • Evaluate and select appropriate algorithms based on business requirements and performance objectives.
  • Continuously improve model accuracy, scalability, and maintainability.

MLOps & Production Engineering
  • Deploy machine learning models into production environments.
  • Build automated model training, validation, deployment, and monitoring pipelines.
  • Implement CI/CD practices for machine learning workflows.
  • Support AI/ML-assisted clustering efforts.
  • Monitor model performance and address model drift, data drift, and operational issues.
  • Maintain model governance, versioning, and documentation standards.

Data Engineering & Platform Integration
  • Collaborate with data engineers to develop scalable data pipelines and feature stores.
  • Integrate machine learning solutions into enterprise applications and business processes.
  • Optimize data processing workflows for large-scale datasets.
  • Ensure data quality, security, and compliance standards are maintained.

Cloud & AI Platforms
  • Develop and deploy solutions using cloud-native AI and machine learning services.
  • Leverage platforms such as Azure Machine Learning, AWS SageMaker, Databricks, Vertex AI, or equivalent technologies.
  • Perform multi-source summarization with human-review workflow by combining AI-driven aggregation of diverse sources with targeted human validation.
  • Utilize distributed computing frameworks to support large-scale analytics workloads.
  • Support enterprise AI strategy and modernization initiatives.

Collaboration & Innovation
  • Partner with business leaders to identify opportunities for AI and advanced analytics solutions.
  • Translate business requirements into machine learning use cases and technical requirements.
  • Stay current on emerging technologies, AI trends, and industry best practices.
  • Contribute to innovation initiatives, proofs of concept, and research activities.

Salary Range: $160,000 - $185,000
General Description of Benefits
  • Top Secret Clearance
  • Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
  • 5+ years of experience in Data Science, Machine Learning Engineering, Artificial Intelligence, or Advanced Analytics.
  • Strong understanding of machine learning algorithms, statistical analysis, and data modeling techniques.
  • Experience building and deploying machine learning models in production environments.
  • Proficiency in Python and machine learning libraries/frameworks.
  • Strong knowledge of SQL and data manipulation techniques.
  • Experience working with large datasets and cloud-based data platforms.
  • Excellent problem-solving, analytical, and communication skills.

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