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Machine Learning Intern Jobs in Michigan (NOW HIRING)

Apex Systems

Machine Learning-Gen Ai

Warren, MI · On-site +1

$107.30K - $128.80K/yr

Job#: 3029488 Machine Learning-Gen Ai/Data Statistics Location: Warren, MI Role Overview An automotive manufacturing client is seeking a Machine Learning Engineer with a foundation in data, deep ...

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Machine Learning Intern information

See Michigan salary details

$22.2K

$37.1K

$76.7K

How much do machine learning intern jobs pay per year?

As of May 28, 2026, the average yearly pay for machine learning intern in Michigan is $37,116.00, according to ZipRecruiter salary data. Most workers in this role earn between $28,300.00 and $40,100.00 per year, depending on experience, location, and employer.

What Does a Machine Learning Intern Do?

A machine learning intern works in the field of data science. During an internship, you work alongside machine learning engineers who are developing artificial intelligence programs. They do this by writing computer code that allows a software system to run autonomously. Your exact responsibilities depend on the type and level of engineering that the company does. While you likely do not have coding duties, you may help the programmers test or debug their code. You may also work with algorithms and the mathematical aspects of artificial intelligence. A machine learning intern works under the supervision of a lead engineer.

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

To thrive as a Machine Learning Intern, you need a solid understanding of statistics, programming (especially Python), and foundational machine learning concepts, typically supported by coursework or a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and data analysis libraries, as well as experience with version control systems like Git, is highly valuable. Strong problem-solving skills, curiosity, and effective communication set outstanding candidates apart in this role. These abilities are essential for analyzing data, building models, and collaborating with teams to develop innovative AI solutions.

What types of projects do Machine Learning Interns typically work on, and how are they supported by the team?

Machine Learning Interns often contribute to real-world projects such as data preprocessing, developing and testing models, or assisting with research for new algorithms. Interns are usually paired with a mentor or work within a small team, receiving guidance during code reviews and regular check-ins. This collaborative environment helps interns gain practical experience, quickly overcome challenges, and integrate feedback, ensuring a steep learning curve and valuable industry exposure.

What is the difference between Machine Learning Intern vs Data Science Intern?

AspectMachine Learning InternData Science Intern
Required CredentialsTypically pursuing or recent graduate in Computer Science, Data Science, or related fields; knowledge of programming and ML frameworksUsually pursuing or recent graduate in Data Science, Statistics, or related fields; strong analytical and programming skills
Work EnvironmentTech companies, research labs, startups focusing on AI/ML projectsBusiness, finance, healthcare, and tech sectors analyzing data for insights
Employer & Industry UsageUsed in companies developing AI products, research institutions, tech startupsCommon in organizations requiring data analysis, reporting, and decision-making support

While both roles involve working with data and programming, a Machine Learning Intern focuses specifically on developing and implementing machine learning models, whereas a Data Science Intern works more broadly on analyzing data, creating reports, and deriving insights. The roles often overlap, but the Machine Learning Intern role emphasizes algorithm development and model deployment.

More about Machine Learning Intern jobs
What are the most commonly searched types of Machine Learning jobs in Michigan? The most popular types of Machine Learning jobs in Michigan are:
What are popular job titles related to Machine Learning Intern jobs in Michigan? For Machine Learning Intern jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Machine Learning Intern jobs in Michigan look for? The top searched job categories for Machine Learning Intern jobs in Michigan are:
What cities in Michigan are hiring for Machine Learning Intern jobs? Cities in Michigan with the most Machine Learning Intern job openings:
Machine Learning Intern jobs near you
Infographic showing various Machine Learning Intern job openings in Michigan as of May 2026, with employment types broken down into 56% Full Time, 26% Part Time, 7% Temporary, 7% Contract, and 4% Nights. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $37,116 per year, or $17.8 per hour.

Machine Learning Engineering Intern

Mariana Minerals

Ann Arbor, MI • On-site

$25 - $35/hr

Internship

Posted 13 days ago

Job description

About Mariana Minerals
Mariana Minerals is a software-first, vertically integrated minerals company on a mission to supply the critical minerals powering modern energy, AI, and defense technologies. We're reimagining the minerals supply chain by combining deep industry expertise with advanced software, automation, and data-driven decision-making.
The Role
We are hiring a Machine Learning Engineering Intern to work on real, high-impact problems within our applied ML and operations team. You will contribute directly to building and improving models that influence real-world industrial systems and decision-making.
This role is designed to provide hands-on experience building and deploying machine learning solutions in production-like environments. You will work closely with engineers and domain experts to understand complex systems and apply ML techniques to improve performance, efficiency, and reliability.
What You'll Do
  • Work on a defined ML project with clear deliverables by the end of the internship
  • Build and experiment with models using Python, PyTorch/TensorFlow, or similar tools
  • Analyze real-world datasets to identify patterns, anomalies, and optimization opportunities
  • Support development of data pipelines, feature engineering, and model evaluation
  • Collaborate with engineers and domain experts to understand system behavior and constraints
  • Run experiments, validate results, and iterate based on findings
  • Document your work and present outcomes and learnings at the end of the internship

Qualification
  • Currently pursuing a degree in Computer Science, Machine Learning, Data Science, Chemical Engineering, or related field
  • Strong fundamentals in machine learning, statistics, and/or data analysis
  • Proficiency in Python and familiarity with ML frameworks (PyTorch, TensorFlow, etc.)
  • Hands-on experience through projects, coursework, or internships
  • Ability to break down problems and execute independently
  • Clear communication skills and willingness to learn in a fast-paced environment

Why Join Us?
At Mariana Minerals, you'll be part of a mission-driven team reshaping the way critical minerals are sourced and supplied globally. You'll have the autonomy to make big decisions, the tools to innovate, and a culture that values ownership, smart automation, and collaboration.
Our culture is built on three principles:
  • Extreme Ownership - We take full responsibility for outcomes, relentlessly driving toward solutions.
  • Engineer Out Requirements, then Automate - We simplify, optimize, and then automate for scale.
  • Share Your Legos - We collaborate openly, share knowledge, and empower each other to build bigger, better solutions.

Join us as we build the future of responsible mineral sourcing and supply.
Mariana is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected status.

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