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Machine Learning Engineer Intern Jobs in Prince George, VA

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 ...

Sr. Lead Machine Learning Engineer (IC)

Richmond, VA ยท On-site +1

$101K - $133K/yr

Sr. 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 ...

New

Sr. Lead Machine Learning Engineer (IC)

Richmond, VA ยท On-site +1

$101K - $133K/yr

Sr. 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 ...

New

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Lead Machine Learning Engineer

Richmond, VA

$101K - $133K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. Our investments in technology infrastructure and world-class ...

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Showing results 1-20

Machine Learning Engineer Intern information

See Prince George, VA salary details

$25.2K

$42K

$86.8K

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

As of Jul 26, 2026, the average yearly pay for machine learning engineer intern in Prince George, VA is $42,007.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,100.00 and $45,400.00 per year, depending on experience, location, and employer.

What types of projects and tasks do Machine Learning Engineer Interns typically work on?

Machine Learning Engineer Interns are often involved in data preparation, feature engineering, model development, and performance evaluation under the guidance of senior engineers or data scientists. You may help implement and test machine learning algorithms, assist in cleaning and visualizing datasets, and contribute to code reviews or research tasks. Interns frequently collaborate with cross-functional teams, such as data scientists, software engineers, and product managers, to solve real-world problems and support ongoing projects. This hands-on experience provides valuable insights into the practical application of machine learning in a professional setting.

What is a Machine Learning Engineer Intern job?

A Machine Learning Engineer Intern is a temporary, entry-level role where individuals work with data scientists and engineers to develop, test, and optimize machine learning models. Interns typically assist in data preprocessing, feature engineering, model training, and evaluation. They may also work on improving existing algorithms, implementing research papers, or deploying models into production. This role provides hands-on experience with machine learning frameworks such as TensorFlow and PyTorch, as well as coding in Python and working with large datasets. The internship helps build practical skills and industry experience in artificial intelligence and data science.

What are the key skills and qualifications needed to thrive in the Machine Learning Engineer Intern position, and why are they important?

To thrive as a Machine Learning Engineer Intern, you need a solid understanding of programming languages such as Python, knowledge of machine learning algorithms, and experience with data analysis, typically supported by coursework in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is often required. Strong problem-solving abilities, attention to detail, and effective communication are valuable soft skills in this role. These competencies enable interns to contribute meaningfully to projects, collaborate efficiently with teams, and adapt in a fast-paced, tech-driven environment.

What cities near Prince George, VA are hiring for Machine Learning Engineer Intern jobs? Cities near Prince George, VA with the most Machine Learning Engineer Intern job openings:

Machine Learning Engineer

WorkNovas LLC

Richmond, VA โ€ข On-site

Contractor

Posted 4 days ago


Job description

Machine Learning Engineer ย 

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
Bachelorโ€™s or Masterโ€™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