Machine Learning Intern Jobs in Michigan
Machine Learning Intern jobs in Michigan are actively sought across automotive technology, health informatics, and university-affiliated research, with demand concentrated among both established industry players and growing startup ecosystems. Detroit, Ann Arbor, and Grand Rapids are the primary hiring metros, where organizations like Ford Motor Company, the University of Michigan, and Rocket Companies recruit interns for roles in computer vision, natural language processing, and predictive modeling. Competition is strongest for candidates who can demonstrate hands-on Python work and prior research exposure. Scan the live roles below and apply to whichever ones fit.
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Job Description
The Role:
As a 2027 Summer Intern on the Vehicle Aerodynamics and Machine Learning team, you will work at the intersection of physics-based vehicle simulation, computational fluid dynamics, scientific machine learning, and aerodynamic design optimization.
You will support research that uses CFD and AI/ML to improve vehicle aerodynamic performance, accelerate design exploration, and enable more efficient development of next-generation vehicles. The work may include analyzing vehicle flow fields, developing data-driven aerodynamic models, evaluating design concepts, and translating research results into practical engineering tools.
This role is intended for an inquisitive, technically motivated student who enjoys applying engineering fundamentals and modern computational methods to complex problems. You will work with experienced researchers and cross-functional engineering partners while developing your skills in vehicle aerodynamics, simulation, machine learning, data analysis, and technical communication.
GM’s related research includes high-fidelity CFD, aerodynamic drag and efficiency improvement, physics-based AI models, surrogate modeling, transfer learning, and rapid aerodynamic feedback from vehicle geometry or design data.
The Team:
The Energy and Propulsion Systems Research team conducts applied research intended to improve vehicle efficiency, performance, range, cost, and sustainability. The team collaborates with researchers, vehicle-development organizations, engineering groups, universities, technology partners, and industry leaders to identify and develop technologies with potential value to GM.
You will work in a multidisciplinary environment that may include vehicle aerodynamicists, CFD specialists, data scientists, machine-learning researchers, vehicle designers, optimization experts, and engineers from propulsion, thermal, body, chassis, and vehicle-performance organizations.
The internship experience may also include innovation challenges, interactions with industry leaders, cross-functional networking events, technical presentations, and community-service activities.
What You’ll Do:
- Support vehicle aerodynamics research involving external flow, aerodynamic drag, lift, downforce, cooling airflow, and vehicle efficiency.
- Set up, run, monitor, and post-process CFD simulations for vehicle and component-level aerodynamic studies.
- Prepare simulation geometry, meshes, boundary conditions, design variables, and analysis workflows.
- Analyze aerodynamic coefficients, pressure distributions, velocity fields, wake structures, flow features, and other performance metrics.
- Build and curate datasets from CFD simulations, experimental results, vehicle geometry, and design variables.
- Develop, train, test, and evaluate machine-learning or surrogate models for aerodynamic quantities and flow-field predictions.
- Investigate physics-informed, data-driven, reduced-order, graph-based, or other scientific machine-learning approaches relevant to vehicle aerodynamics.
- Apply data preprocessing, feature engineering, dimensionality reduction, model selection, hyperparameter tuning, and validation techniques.
- Evaluate model accuracy, robustness, generalization, uncertainty, and limitations across vehicle geometries and operating conditions.
- Compare ML predictions with CFD, wind-tunnel, experimental, or other trusted engineering results.
- Support design-of-experiments, surrogate-based optimization, sensitivity studies, and aerodynamic shape exploration.
- Develop Python-based scripts, tools, and workflows to automate simulation setup, data processing, model training, visualization, and reporting.
- Help identify opportunities to reduce analysis time and enable earlier aerodynamic feedback during vehicle design.
- Document assumptions, methods, data sources, model configurations, results, limitations, and recommendations.
- Create clear plots, visualizations, technical reports, presentations, and demonstrations for engineering and research audiences.
- Collaborate with researchers and cross-functional partners to define technical questions, review results, and recommend next steps. Present technical findings and participate in innovation, networking, and professional-development activities.
Required Qualifications:
- Pursuit of an advanced degree (MS or PhD) in mechanical engineering, aerospace engineering, computational engineering, computer science, applied mathematics, physics, data science, or a related technical discipline. Able to work fulltime, 40 hours per week during the summer months.
Preferred Qualifications:
- Coursework, research, or project experience in fluid mechanics, vehicle aerodynamics, computational fluid dynamics, turbulence modeling, numerical methods, optimization, or heat transfer.
- Experience with Python, MATLAB, C++, or comparable programming languages.
- Experience with NumPy, pandas, SciPy, scikit-learn, PyTorch, TensorFlow, or similar scientific-computing and machine-learning libraries.
- Familiarity with CFD, CAE, CAD, meshing, visualization, Linux, high-performance computing, or engineering software workflows.
- Experience developing or applying machine-learning models to scientific, engineering, physical-simulation, or time-series data.
- Familiarity with surrogate modeling, physics-informed machine learning, graph neural networks, neural operators, transfer learning, uncertainty quantification, or model explainability.
- Experience with design-of-experiments, parameter studies, optimization, or automated engineering workflows.
- Ability to evaluate data quality, identify modeling limitations, and distinguish physically meaningful results from numerical or data artifacts.
- Experience communicating technical results through reports, presentations, plots, code documentation, or demonstrations.
- Strong analytical, written, and verbal communication skills. Ability to work independently while collaborating effectively with researchers and cross-functional engineering teams.
GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc.).
Work Arrangement:
This role is categorized as hybrid. This means the successful candidate is expected to report to Warren, MI three times per week, at minimum [or other frequency dictated by the business]
Start dates for this internship role are May 24th & June 14th of 2027.




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We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire .
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See All 16 Machine Learning Intern Jobs in Michigan
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Find Machine Learning Intern JobsMachine Learning Intern Jobs by City in Michigan
Where Michigan roles are concentrated, by current openings.
Machine Learning Intern Job Market in Michigan
A snapshot from current Michigan openings, updated as new roles post.
Who's Hiring



Top Industries Hiring
- Automotive
- Science & Research
What Michigan Employers Look For
The qualifications that appear most often in machine learning intern jobs across Michigan.
- Currently enrolled in a bachelor's or master's degree program in computer science or related field
- Proficiency in Python and at least one machine learning framework such as TensorFlow or PyTorch
- Familiarity with data preprocessing, model training, and evaluation methodologies
- Experience with statistical analysis and working knowledge of linear algebra and calculus
- Ability to collaborate on cross-functional teams and communicate technical findings clearly
- Exposure to cloud platforms such as AWS, Azure, or Google Cloud is preferred by most Michigan employers
Machine Learning Intern Jobs in Michigan: Frequently Asked Questions
How do you become a machine learning intern in Michigan?
Becoming a machine learning intern in Michigan typically requires current enrollment in a computer science, data science, or engineering program at a Michigan university such as the University of Michigan, Michigan State University, or Michigan Technological University. No state-issued license is required for this role. Building a portfolio of applied projects on platforms like GitHub and participating in campus research labs or hackathons strengthens applications considerably for Michigan employers.
Which companies hire machine learning interns in Michigan?
Michigan machine learning intern roles are posted by General Motors (GM), Lucid Motors, and May Mobility and others right now, based on current listings on Migrate Mate as of November 2026. Michigan's strong automotive and mobility sector means many internships are tied to companies developing autonomous vehicle systems, predictive maintenance tools, and connected-car software.
Which Michigan cities have the most machine learning intern jobs?
Ann Arbor, Warren, and Detroit have the most machine learning intern openings in Michigan. Detroit anchors the list through its large automotive and technology employers, Ann Arbor benefits from its dense concentration of University of Michigan research groups and spin-off companies, and Grand Rapids attracts interns through its growing health technology and manufacturing analytics sectors.
Are there remote machine learning intern jobs in Michigan?
Yes, and more than most fields, since machine learning work is largely code- and data-based and does not require physical presence. About 20% of machine learning intern openings tied to Michigan are remote or hybrid as of November 2026, reflecting how readily this type of work transfers online. Roles focused on data pipeline work and model experimentation are most commonly offered in fully remote formats, while positions requiring collaboration with hardware or embedded systems teams tend to be on-site.
How can I get hired as a machine learning intern in Michigan with little or no experience?
The most realistic entry path is applying through university research lab positions at Michigan State University, the University of Michigan, or Wayne State University, which regularly place students with no industry history into structured internship pipelines. Large Michigan employers such as Ford and General Motors run formal early-career and co-op programs designed for students who lack prior industry experience. Building a few public GitHub projects using open datasets and contributing to faculty-led research establishes the portfolio evidence Michigan hiring managers look for most.
Where can I find and apply to machine learning intern jobs in Michigan?
You can find and apply to machine learning intern jobs in Michigan on Migrate Mate, which lists current Michigan openings updated regularly. Search the available roles, identify the ones that match your skills and location preferences, and apply directly to each position that fits.
See All 16 Machine Learning Intern Jobs in Michigan
Find roles in Michigan that match your experience and apply in just a few clicks.
Find Machine Learning Intern Jobs