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Junior Machine Learning Engineer Jobs in Virginia

We are seeking an earlycareer Machine Learning Engineer who is excited to grow rapidly by building and deploying productiongrade ML systems. The ideal candidate has a strong engineering mindset, has ...

Richmond VA As a Machine Learning Engineer,you will: Day to Day Responsibilities * Design and implement agentic AI systems capable of planning, tool use, memory, and multi-step reasoning * Build and ...

We are seeking an early-career Machine Learning Engineer who is excited to grow rapidly by building and deploying production-grade ML systems. The ideal candidate has a strong engineering mindset ...

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Lead Machine Learning Engineer

Fort Belvoir, VA · On-site

$115K - $152K/yr

Role: Lead Machine Learning Engineer Location: Ft. Belvoir, VA (On-site with Hybrid Option ... Abilty to mentor and coach junior resources with delivery tasks. * Self-motivated, with the ability ...

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Lead Machine Learning Engineer

Mclean, VA · On-site

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Machine Learning Engineer

Arlington, VA · Hybrid

$110K - $160K/yr

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Machine Learning Engineer

Arlington, VA · Hybrid

$110K - $160K/yr

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

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Junior Machine Learning Engineer information

See Virginia salary details

$33.2K

$71.2K

$108.6K

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

As of Jun 11, 2026, the average yearly pay for junior machine learning engineer in Virginia is $71,184.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,100.00 and $79,300.00 per year, depending on experience, location, and employer.

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

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

What kinds of projects and responsibilities can a Junior Machine Learning Engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

What engineers make $500,000?

Senior engineers in fields such as software, data engineering, and specialized roles like machine learning engineers can earn $500,000 or more annually, especially with extensive experience, advanced skills, and in high-demand industries. Compensation often includes base salary, bonuses, and stock options, particularly at large tech companies or startups with significant funding.

How much does a junior ML engineer earn?

A junior machine learning engineer typically earns between $60,000 and $90,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.

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

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

What does a Junior Machine Learning Engineer do?

A Junior Machine Learning Engineer assists in developing, testing, and deploying machine learning models under the supervision of senior engineers or data scientists. Their responsibilities often include data preprocessing, feature engineering, and implementing algorithms using frameworks like TensorFlow or PyTorch. They also help maintain data pipelines and ensure models perform efficiently in production environments. This role is typically entry-level, providing valuable hands-on experience in applying machine learning concepts to real-world problems.

Which 5 jobs will survive AI?

For a Junior Machine Learning Engineer, roles that require complex problem-solving, creativity, and human interaction are more likely to persist alongside AI advancements. These include jobs in healthcare, education, research, specialized technical fields, and management, where human judgment and empathy remain essential. Developing skills in domain expertise, critical thinking, and interdisciplinary knowledge can help ensure long-term employability in an evolving AI landscape.

Can I learn ML in 3 months?

Learning machine learning as a Junior Machine Learning Engineer in three months is possible for individuals with prior programming experience and a strong foundation in mathematics. Focused study on core concepts, practical projects, and familiarity with tools like Python and scikit-learn can help build foundational skills within this timeframe, but mastering advanced topics typically requires longer-term experience. Real-world proficiency often depends on ongoing practice and continuous learning beyond initial training.

What Does a Junior Machine Learning Engineer Do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

What are the most commonly searched types of Machine Learning Engineer jobs in Virginia? The most popular types of Machine Learning Engineer jobs in Virginia are:
What cities in Virginia are hiring for Junior Machine Learning Engineer jobs? Cities in Virginia with the most Junior Machine Learning Engineer job openings:
Machine Learning Engineer

Other

Posted 29 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.