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Machine Learning Intern Jobs in Minnesota City, MN

Trane Technologies plc

Intern-Technician

La Crosse, WI · On-site

$22/hr

Trane Technologies has an exciting opportunity for an onsite position in our Engineering Test Laboratory (Lab) in La Crosse, Wisconsin as an HVAC Product Development Technician Intern. Your primary ...

Trane Technologies plc

Intern-Technician

La Crosse, WI · On-site

$22/hr

Trane Technologies has an exciting opportunity for an onsite position in our Engineering Test Laboratory (Lab) in La Crosse, Wisconsin as an HVAC Product Development Technician Intern. Your primary ...

Minnehaha County

Wabasha County Intern

Wabasha, MN · On-site

$14.75 - $19.75/hr

* applicants must have strong writing, communication, and critical thinking skills, as well as a solid understanding of the field of Public Health or Emergency Management. * While experience is not ...

All JobsMachine Learning Intern JobsMachine Learning Intern Jobs in Minnesota City, MN

Machine Learning Intern information

See Minnesota City, MN salary details

$27.6K

$46K

$95.1K

How much do machine learning intern jobs pay per year?

As of Sep 5, 2026, the average yearly pay for machine learning intern in Minnesota City, MN is $46,019.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,100.00 and $49,700.00 per year, depending on experience, location, and employer.

What does a machine learning intern do?

A Machine Learning Intern assists with developing, testing, and deploying machine learning models under the supervision of experienced data scientists or engineers. Their responsibilities may include data preprocessing, feature engineering, coding algorithms, analyzing results, and assisting with research tasks. Interns often work with programming languages like Python and libraries such as TensorFlow or PyTorch. The internship provides hands-on experience in real-world machine learning projects and helps interns build essential skills for a future career in the field.

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 job categories do people searching Machine Learning Intern jobs in Minnesota City, MN look for?

The top searched job categories for Machine Learning Intern jobs in Minnesota City, MN are:

What cities near Minnesota City, MN are hiring for Machine Learning Intern jobs?

Cities near Minnesota City, MN with the most Machine Learning Intern job openings:

Machine Learning Intern jobs near you

Intern, Energy Data Science

Dairyland Power Cooperative

La Crosse, WI • On-site

$30/hr

Part-time

This job post has expired today. Applications are no longer accepted.

Job description

Hourley Wage: $30.00
PURPOSE: The Energy Data Science Intern will support strategic decision making by increasing data accessibility, performing statistical analysis, building predictive models, and providing actionable insights. This position advances all DPC's strategic priorities, but most notably our commitment to financial strength, growth & innovation, and our safety culture.
ESSENTIAL JOB FUNCTIONS:
Build, test and document data pipelines that ingest, transform and deliver data for analysis and reporting. Assist with integrating APIs, databases, enterprise applications and external data sources into Dairyland Power Cooperative's cloud-based Lakehouse environment. Clean, validate and organize energy and business data to improve reliability and accessibility. Perform statistical analysis to identify trends, quantify uncertainty and support business decisions. Develop and evaluate machine learning models for defined business applications. Support model deployment, validation, performance monitoring and ongoing improvement. Translate business questions into quantitative analyses. Present findings, assumptions and recommendations clearly to technical and nontechnical audiences. Create technical documentation for data sources, pipelines, models and analytical methods. Perform other duties as assigned.
MINIMUM QUALIFICATIONS:
Education & Experience: Currently pursuing either an undergraduate or graduate degree in data science, statistics, mathematics, artificial intelligence, computer science, or another related field.
Skills:
  • Experience using at least one scientific computing language, preferably Python
  • Foundational knowledge of data structures, statistical analysis and relational databases
  • Strong analytical, problem-solving and organizational skills
  • Strong verbal, written and interpersonal communication skills
  • Ability to work independently.

PREFERRED QUALIFICATIONS:
  • Experience with SQL and data modeling
  • Experience building data pipelines or integrating APIs
  • Familiarity with Microsoft Fabric, AWS or another cloud data platform
  • Familiarity with machine learning model development, validation, and deployment
  • Experience with Power BI or another data visualization tool
  • Experience using Git or another version control system

Licenses and Certifications: Valid Driver's License
Physical Demands: The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. While performing the duties of this job, the employee is regularly required to talk or hear. The employee frequently is required to stand; walk; use hands to finger, handle or feel; and reach with hands and arms.
Environmental Demands: Normal work schedule is indoors.
Other Job Characteristics: Travel required, occasionally overnight. Works with limited supervision in a variably paced, variable pressure setting. Handles multiple priorities.

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