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Machine Learning Winter Internship Jobs in Maryland

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Machine Learning Winter Internship information

What types of projects and tasks can I expect to work on during a machine learning winter internship?

During a Machine Learning Winter Internship, you can expect to work on hands-on projects such as data preprocessing, building and evaluating machine learning models, and assisting with research experiments. Interns often contribute to real-world applications, such as developing predictive analytics tools, optimizing algorithms, or supporting deployment efforts. Collaboration is common, as you'll work closely with data scientists, engineers, and sometimes product teams, giving you exposure to the full machine learning workflow. This environment provides an excellent opportunity to apply theoretical knowledge, gain practical experience, and build a professional network in the field.

What is a machine learning winter internship?

A Machine Learning Winter Internship is a short-term, practical training program typically offered during the winter months for students or early-career professionals interested in machine learning. Interns work on real-world projects involving data analysis, model development, and algorithm implementation under the guidance of experienced mentors. The internship provides hands-on experience with tools and techniques used in the field, helping participants build technical skills and gain industry exposure. These positions are often offered by tech companies, research labs, or startups and can be either remote or onsite. Successful completion of a machine learning internship can enhance a candidate's resume and open up further career opportunities in artificial intelligence and data science.

What are the key skills and qualifications needed to thrive as a machine learning winter intern, and why are they important?

To thrive as a Machine Learning Winter Intern, you generally need a solid foundation in mathematics, programming (especially Python), and a basic understanding of machine learning concepts, often acquired through coursework or relevant projects. Familiarity with tools such as TensorFlow, PyTorch, and data analysis libraries like Pandas and NumPy is typically required. Strong problem-solving abilities, collaboration, and curiosity help interns stand out in team-based, fast-paced environments. These skills are crucial for effectively contributing to real-world projects and quickly learning from experienced professionals during the internship.

What is the difference between Machine Learning Winter Internship vs Data Science Winter Internship?

AspectMachine Learning Winter InternshipData Science Winter Internship
Required CredentialsUndergraduate or graduate in CS, AI, or related fields; some knowledge of ML frameworksUndergraduate or graduate in Statistics, Math, CS; familiarity with data analysis tools
Work EnvironmentResearch labs, tech companies, startups focusing on ML modelsData analysis, visualization, and interpretation in various industries
Employer & Industry UsageTech firms, AI startups, research institutionsTech companies, finance, healthcare, consulting

While both internships involve working with data, the Machine Learning Winter Internship emphasizes developing and applying ML algorithms, whereas the Data Science Winter Internship focuses on analyzing data, creating reports, and deriving insights. Candidates should choose based on their specific skills and career goals in AI or data analysis.

What job categories do people searching Machine Learning Winter Internship jobs in Maryland look for? The top searched job categories for Machine Learning Winter Internship jobs in Maryland are:
What cities in Maryland are hiring for Machine Learning Winter Internship jobs? Cities in Maryland with the most Machine Learning Winter Internship job openings:

Artificial Intelligence/Machine Learning Engineer, Junior

EverWatch

Annapolis Junction, MD • On-site

Full-time

Re-posted 11 days ago


Job description

Job Summary:
EverWatch is a government solutions company providing advanced defense, intelligence, and deployed support to our country’s most critical missions. The AI/ML Engineer will develop and deploy artificial intelligence and machine learning solutions to enhance operational workflows and support decision-making in secure environments.
Responsibilities:
• Cyber and intelligence analysts rely on multi-step workflows that are time-sensitive, detail-rich, and critical to national security.
• As an AI/ML Engineer at EverWatch Solutions, you will work directly with mission users to develop and deploy artificial intelligence and machine learning solutions that enhance operational workflows, improve data accessibility, and support rapid decision-making in secure environments.
• You will collaborate with operators, analysts, software developers, and mission leadership to capture operational needs and translate them into effective AI-enabled capabilities.
• Your work may include developing LLM-powered workflows, agent-based automation, and other AI/ML solutions that streamline analytical tasks and improve mission effectiveness.
• You will support the integration of AI capabilities into existing operational systems while ensuring solutions are reliable, scalable, and compliant with security and governance requirements in classified environments.
• Additionally, you will contribute to data pipeline development, model evaluation, workflow optimization, and operational testing to support production-ready AI solutions.
Qualifications:
Required:
• 1-4 years of experience with Python for data analysis and machine learning tasks through academic, internship, or project-based work
• Knowledge of machine learning concepts including supervised learning, model evaluation, and data preprocessing
• Familiarity with standard data science libraries and development tools
• Ability to think analytically, solve problems effectively, and learn quickly in a fast-paced, mission-oriented environment
• Ability to collaborate within a team and communicate technical concepts clearly
• TS/SCI clearance with a polygraph
• Bachelor’s degree in computer science, Data Science, Electrical Engineering, Mathematics, Statistics, or a related technical field or master’s degree with limited experience
Preferred:
• Experience with academic coursework, thesis work, or capstone projects involving machine learning, natural language processing, or data science applications
• Experience with version control tools such as Git and collaborative development environments
• Knowledge of deep learning frameworks such as PyTorch or TensorFlow
• Knowledge of large language models (LLMs) and generative AI concepts
• Knowledge of cloud platforms such as AWS, Azure, or GCP
• Knowledge of containerization technologies such as Docker or Kubernetes
• Knowledge of agentic AI, retrieval-augmented generation (RAG), or other applied NLP techniques
• Prior internship, co-op, research, or project experience supporting government, defense, or intelligence community environments
Company:
EverWatch focuses on in-house investment management. Founded in 1999, the company is headquartered in West Palm Beach, USA, with a team of 201-500 employees. The company is currently Growth Stage.