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Machine Learning Developer Intern Jobs in Virginia

SAIC

Machine Learning Developer

Arlington, VA · Hybrid

The Machine Learning Developer will collaborate with software engineers to create innovative ML/AI solutions, improve predictive models, and deploy machine learning systems into production. Key ...

SAIC

Machine Learning Developer

Arlington, VA · Hybrid

The Machine Learning Developer will collaborate with software engineers to create innovative ML/AI solutions, improve predictive models, and deploy machine learning systems into production. Key ...

SAIC

Machine Learning Developer

Arlington, VA · On-site

The Machine Learning Developer will collaborate with software engineers to create innovative ML/AI solutions, improve predictive models, and deploy machine learning systems into production. Key ...

Full Scope

Machine Learning Engineer

Reston, VA

Machine Learning Engineer Location: Fort Meade, MD Required Clearance : TS/SCI w/ Full-Scope Poly Salary: Competitive We are seeking a highly skilled and motivated Machine Learning Engineer to join ...

Samprasoft

Machine Learning Engineer

Mclean, VA

GCP/AWS Machine Learning Engineer Freddie Mac iLab is currently looking for Machine Learning Engineers in its Innovation Labs - Tech Strategy team. In this position, you will be responsible for ...

ICONMA

Machine Learning Engineer

Mclean, VA

Machine Learning Engineer Our client, a financial company, is looking for a Machine Learning Engineer for their McLean, VA location. Requirements: * Python, AWS, Kubernetes, Kubeflow, MLOps, ML ...

ManTech

Machine Learning Engineer

Herndon, VA

The Machine Learning Engineer will leverage their strong technical background and knowledge to support highly scalable machine learning-based applications, including both pipelines and services ...

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Machine Learning Developer Intern information

How do Machine Learning Developer Interns typically collaborate with data scientists and engineers during their internship?

Machine Learning Developer Interns often work closely with data scientists to understand the problem domain, gather relevant datasets, and select appropriate models. They also collaborate with software engineers to integrate machine learning solutions into existing systems, ensuring scalability and performance. Regular communication through stand-up meetings, code reviews, and collaborative platforms is common, allowing interns to learn best practices and receive feedback on their work. This teamwork not only enhances technical skills but also provides valuable exposure to real-world deployment and project lifecycle management.

What does a Machine Learning Developer Intern do?

A Machine Learning Developer Intern assists with developing, testing, and implementing machine learning models and algorithms under the guidance of experienced engineers or data scientists. Their tasks may include data preprocessing, model training, evaluating model performance, and helping deploy models into production environments. Interns often collaborate with team members to solve real-world problems using machine learning techniques and may also assist in researching new methodologies or optimizing existing solutions. This role provides hands-on experience in coding, data analysis, and applying theoretical concepts to practical scenarios.

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

To thrive as a Machine Learning Developer Intern, you need a solid understanding of programming (especially Python), statistics, and machine learning concepts, often supported by coursework or relevant project experience. Familiarity with ML frameworks like TensorFlow or PyTorch, and tools such as Jupyter Notebooks and version control systems like Git, is typically expected. Strong analytical thinking, eagerness to learn, and effective communication help interns contribute to team projects and adapt quickly. These skills are essential for solving real-world problems, collaborating with teams, and building a foundation for a successful career in machine learning.

What is the difference between Machine Learning Developer Intern vs Data Scientist Intern?

AspectMachine Learning Developer InternData Scientist Intern
Required CredentialsTypically pursuing or recently completed a degree in Computer Science, Data Science, or related fields; knowledge of programming languages like Python or JavaSimilar educational background; strong skills in statistics, programming, and data analysis
Work EnvironmentHands-on experience with ML models, algorithms, and software development in tech or research settingsData analysis, visualization, and interpretation in business or research contexts
Employer & Industry UsageTech companies, startups, research labs focusing on AI/ML projectsBusiness, finance, healthcare, and research organizations analyzing large datasets

Both roles involve working with data and programming, but Machine Learning Developer Interns focus more on building and deploying ML models, while Data Scientist Interns emphasize data analysis and insights. The roles often overlap, especially in tech environments, but their core tasks differ slightly.

What cities in Virginia are hiring for Machine Learning Developer Intern jobs? Cities in Virginia with the most Machine Learning Developer Intern job openings:
Machine Learning Developer Intern jobs near you
Machine Learning Developer

Machine Learning Developer

SAIC

Arlington, VA • Hybrid

Full-time

Posted 2 days ago

SAIC rating

7.8

Company rating: 7.8 out of 10

Based on 78 frontline employees who took The Breakroom Quiz

70th of 203 rated it services

Job description

Job ID: 2611091

Location: Arlington, VA, US

Date Posted: 2026-05-05

Category: Software

Subcategory: SW Engineer

Schedule: Full-Time

Shift: Day Job

Travel: Yes - 10% of the time

Minimum Clearance Required: Secret

Clearance Level Must Be Able to Obtain: None

Potential for Remote Work: ORA_HYBRID


Description

SAIC is seeking a talented and experienced Machine Learning Developer to join our dynamic team.

This position is hybrid in Arlington, VA with 2-3 days per week onsite at the Pentagon or the Mark Center.

The ideal candidate will have a strong background in computer science, software engineering, and experience with machine learning algorithms and frameworks. The Machine Learning Developer will collaborate with software engineers to create innovative ML/AI solutions, improve predictive models, and deploy machine learning systems into production.

Key Responsibilities:

  • Develop and implement machine learning models and algorithms to provide suggested values to readiness reports for our DOD client.
  • Refine data collection processes and improve data quality.
  • Design and develop scalable machine learning solutions for various applications.
  • Work with software developers to integrate machine learning models into production systems.
  • Conduct research to identify new approaches and methods for machine learning and AI.
  • Stay updated with the latest trends and advancements in machine learning and AI.
  • Document processes, codes, and workflows for future reference and reproducibility.
  • Provide support and maintenance for deployed machine learning systems. 

Qualifications

Required Education:

  • Bachelors and five (5) years or more experience; Masters and three (3) years or more experience; PhD and zero (0) years related experience; four (4) years of experience considered in lieu of degree.

Qualifications:

  • Proven experience designing, developing, and deploying OpenAI solutions as a Machine Learning Developer or in a similar role.
  • Strong programming skills in Python, R, C#, Java or similar languages.
  • Experience with deep learning techniques and models.
  • Expertise in natural language processing (NLP) or computer vision.
  • Proficiency with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-Learn, etc.
  • Experience with data preprocessing, data mining, and data visualization techniques.
  • Strong analytical and problem-solving skills.
  • Excellent communication and teamwork abilities.
  • Familiarity with software development best practices and source control (e.g., Git).

Clearance:

  • Active Secret clearance is required for this position.

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