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Junior Machine Learning Engineer Jobs in Virginia

WorkNovas LLC

Machine Learning Engineer

Richmond, VA · On-site

Machine Learning Engineer Richmond, Virginia (5 Days Onsite) need local within commute About the Role We are seeking a Machine Learning Engineer with expertise in agentic AI systems to design, build ...

TheIncLab

Senior Machine Learning Engineer

Mclean, VA · On-site

$105K - $145K/yr

Mentor junior engineers and guide best practices in ML development Stay current with emerging ML ... Strong understanding of machine learning theory and fundamentals * Model selection and evaluation

TheIncLab

Senior Machine Learning Engineer

Mclean, VA · On-site

$105K - $145K/yr

Mentor junior engineers and guide best practices in ML development Stay current with emerging ML ... Strong understanding of machine learning theory and fundamentals * Model selection and evaluation

TheIncLab

Senior Machine Learning Engineer

Mclean, VA · On-site

$105K - $145K/yr

Mentor junior engineers and guide best practices in ML development Stay current with emerging ML ... Strong understanding of machine learning theory and fundamentals * Model selection and evaluation

Elder Research

Machine Learning Engineer

Chantilly, VA · On-site

Machine Learning Engineer General Information Requisition #728 Locations USA-VA-Chantilly Posting Date 07/24/2026 Security Clearance Required - TS/SCI + CI Poly Remote Type N/A Time Type Full time ...

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 technology teams to help clinical, operational, and financial partners solve advanced analytical problems.

Capital One

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 ...

Capital One

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 ...

Hirekeyz Inc

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 ...

Capital One

Lead Machine Learning Engineer (IC)

Richmond, VA · On-site +1

$101K - $133K/yr

Lead Machine Learning Engineer (IC) 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.

New

Capital One

Lead Machine Learning Engineer (IC)

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer (IC) 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.

New

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All JobsMachine Learning Engineer JobsJunior Machine Learning Engineer JobsJunior Machine Learning Engineer Jobs in Virginia

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 Aug 6, 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 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?

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.

More about Junior Machine Learning Engineer jobs
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 are popular job titles related to Junior Machine Learning Engineer jobs in Virginia? For Junior Machine Learning Engineer jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Junior Machine Learning Engineer jobs in Virginia look for? The top searched job categories for Junior 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:
Junior Machine Learning Engineer jobs near you
Infographic showing various Junior Machine Learning Engineer job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $71,184 per year, or $34.2 per hour.

Machine Learning Engineer

WorkNovas LLC

Richmond, VA • On-site

Contractor

Re-posted 14 days ago

Job description

Machine Learning Engineer  

Richmond, Virginia (5 Days Onsite) need local within commute

About the Role
We are seeking a Machine Learning Engineer with expertise in agentic AI systems to design, build, and deploy next-generation AI solutions. In this role, you will work at the intersection of LLMs, autonomous agents, retrieval-augmented generation (RAG), and enterprise-scale systems, leveraging Azure AI Foundry, Copilot Studio, and modern orchestration frameworks.
You will collaborate closely with product managers, architects, and application teams to deliver intelligent, production-grade AI agents that integrate seamlessly with business workflows and enterprise data.
Key Responsibilities
Design and implement agentic AI systems capable of planning, tool use, memory, and multi-step reasoning
Build and deploy AI solutions using Azure AI Foundry and Copilot Studio
Develop RAG pipelines integrating structured and unstructured enterprise data
Implement and optimize vector databases for semantic search and long-term agent memory
Orchestrate LLM-based agents using frameworks such as LangChain (or equivalent)
Develop scalable backend services and APIs using Python
Integrate AI agents with enterprise tools, APIs, and workflows
Evaluate, monitor, and optimize agent performance, reliability, and cost
Apply responsible AI principles including security, privacy, and governance
Stay current with advancements in LLMs, agent architectures, and Azure AI services
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
5+ years of experience in machine learning, AI engineering, or applied ML
Strong proficiency in Python for ML and backend development
Hands-on experience building LLM-based applications
Practical experience with agentic AI patterns (tool calling, planning, memory, reflection)
Experience with LangChain or similar agent orchestration frameworks
Solid understanding of RAG architectures
Experience with vector databases (e.g., Azure AI Search, Pinecone, etc.)
Familiarity with Azure cloud services and enterprise-grade deployments
Hands-on experience with MCP and/or A2A agent communication frameworks
Preferred Qualifications
Direct experience with Azure AI Foundry and Copilot Studio
Experience integrating AI agents into enterprise workflows or SaaS platforms
Knowledge of prompt engineering, evaluation frameworks, and guardrails
Experience with CI/CD, MLOps, or AI observability
Understanding of security, identity, and compliance in enterprise AI systems
Nice-to-Have
Contributions to AI prototypes, internal platforms, or open-source projects
Experience moving AI solutions from prototype to production
Strong communication skills and ability to explain complex AI systems to non-experts