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Machine Learning Engineer Intern Jobs in Baltimore, MD

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Machine Learning Engineer Intern information

See Baltimore, MD salary details

$25.3K

$42.3K

$87.4K

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

As of May 30, 2026, the average yearly pay for machine learning engineer intern in Baltimore, MD is $42,311.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,300.00 and $45,700.00 per year, depending on experience, location, and employer.

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 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.
More about Machine Learning Engineer Intern jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Baltimore, MD? The most popular types of Machine Learning Engineer jobs in Baltimore, MD are:
What are popular job titles related to Machine Learning Engineer Intern jobs in Baltimore, MD? For Machine Learning Engineer Intern jobs in Baltimore, MD, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Intern jobs in Baltimore, MD look for? The top searched job categories for Machine Learning Engineer Intern jobs in Baltimore, MD are:
What cities near Baltimore, MD are hiring for Machine Learning Engineer Intern jobs? Cities near Baltimore, MD with the most Machine Learning Engineer Intern job openings:
Machine Learning Engineer Intern jobs near you
Infographic showing various Machine Learning Engineer Intern job openings in Baltimore, MD as of May 2026, with employment types broken down into 92% Full Time, 7% Part Time, and 1% Contract. Highlights an 69% Physical, 1% Hybrid, and 30% Remote job distribution, with an average salary of $42,311 per year, or $20.3 per hour.
Machine Learning Engineer

Machine Learning Engineer

Maverc Technologies

Columbia, MD

Full-time

Posted 10 days ago

Job description

Become part of a team solving the most significant Cybersecurity & IT Challenges and helping keep the world’s largest and most elite brands safer from cyber threats. At Maverc we have a powerful mindset based on our core values of being accountable, helpful, adaptable, and focused. Maverc Technologies is a proven and effective small business partner and consultant, recognized as a leader in providing cyber security and IT services to the Federal, State, and local Government and within the Intelligence Community. Maverc Technologies is seeking an Machine Learning Engineer to support one of our corporate customers.



Job Duties and Responsibilities 

A talented Machine Learning Engineer to support our AI Center of Excellence! In this role, you and your team will be responsible for the entire lifecycle of machine learning models, from managing and deploying them to troubleshooting any pipeline issues that arise. We offer a collaborative environment where you will work closely with engineers and data scientists to bring impactful ML solutions to life.

Responsibilities include, but are not limited to:

  • Manage and deploy machine learning models into production
  • Debug and troubleshoot issues with deployment pipelines
  • Utilize and understand core ML tooling
  • Work with dataframes to manipulate and prepare data for models
  • Collaborate with the various teams within the AI Center of Excellence to ensure successful model implementation
  • Analyze large amounts of information to discover trends and patterns
  • Build predictive models and machine-learning algorithms


QUALIFICATIONS AND EXPERIENCE 

  • Active SECRET
  • US Citizenship
  • Minimum of 8 years’ experience in DevOps or MLOps
  • Understanding of machine learning modeling techniques and algorithms
  • Experience with Python, Docker, Kubernetes and Git
  • Skilled in common data science libraries (Scikit-learn, PyTorch, etc)
  • Strong math skills (e.g. statistics, algebra)
  • Problem-solving aptitude
  • Excellent communication and presentation skills
  • Experience with deploying open-source LLMs
  • DataBricks
  • Splunk
  • Continuous Integration/Continuous Deployment
  • Knowledge of statistics and concepts in neural networks


Education: Bachelor’s or Master’s in Computer Science, Computer Engineering, or other related field.


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