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Machine Learning Co Op Jobs (NOW HIRING)

Atlas Roofing Corporation

Data Engineer Co-Op

Meridian, MS · On-site

$21 - $25/hr

Design, develop, and deploy machine learning models to support predictive analytics, classification ... Data Engineer Co-op Required Skills & Qualifications * Second-semester freshman standing or higher ...

True Manufacturing

AI Analyst Co-op

O Fallon, MO · Hybrid

We are seeking a motivated AI Analyst Co-op to join our team and support the design, development, and deployment of artificial intelligence and machine learning solutions. This role offers hands-on ...

True Manufacturing

AI Analyst Co-op

O Fallon, MO · On-site

$23/hr

We are seeking a motivated AI Analyst Co-op to join our team and support the design, development, and deployment of artificial intelligence and machine learning solutions. This role offers hands-on ...

True Manufacturing

AI Analyst Co-op

O Fallon, MO · Hybrid

$23/hr

We are seeking a motivated AI Analyst Co-op to join our team and support the design, development, and deployment of artificial intelligence and machine learning solutions. This role offers hands-on ...

True Manufacturing

AI Analyst Co-op

O Fallon, MO · Hybrid

We are seeking a motivated AI Analyst Co-op to join our team and support the design, development, and deployment of artificial intelligence and machine learning solutions. This role offers hands-on ...

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Machine Learning Co Op information

See salary details

$25.5K

$42.6K

$88K

How much do machine learning co op jobs pay per year?

As of Jun 9, 2026, the average yearly pay for machine learning co op in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is the difference between Machine Learning Co Op vs Data Scientist?

AspectMachine Learning Co OpData Scientist
Required CredentialsTypically pursuing a degree in CS, Data Science, or related fields; internships often preferredUsually holds a bachelor's or master's in Data Science, Statistics, or related fields; advanced certifications beneficial
Work EnvironmentInternship setting, often part-time or seasonal, in tech or research companiesFull-time role in various industries, including tech, finance, healthcare, with collaborative teams
Employer & Industry UsageUsed by companies for training and evaluating potential future employees; common in tech and research sectorsHired for analyzing data, building models, and deriving insights; prevalent across multiple industries

While both roles involve working with data and algorithms, a Machine Learning Co Op is typically an internship aimed at gaining experience, whereas a Data Scientist is a full-time professional responsible for developing and deploying data models. The Co Op provides a stepping stone into the field, often leading to a full-time Data Scientist position.

What types of projects do Machine Learning Co-Op students typically work on, and how do they contribute to the team?

Machine Learning Co-Op students often work on a variety of hands-on projects, such as developing data preprocessing pipelines, training and evaluating machine learning models, or supporting ongoing research initiatives. They commonly collaborate with data scientists, engineers, and other interns, contributing fresh perspectives and technical support. Co-Ops may also participate in code reviews, attend team meetings, and present their findings, making them valuable contributors to both experimental and production-level work. This collaborative environment offers plenty of opportunities to learn from experienced professionals while making a real impact on projects.

What is a Machine Learning Co-Op?

A Machine Learning Co-Op is a temporary, paid position that allows students or recent graduates to gain hands-on experience working with machine learning technologies in a professional setting. Co-ops typically last several months and are designed to provide practical exposure to real-world projects, such as building models, analyzing data, and collaborating with data scientists or engineers. This role helps participants develop technical skills, gain industry insights, and build a professional network, which can be valuable for future career opportunities in the field of artificial intelligence or data science.

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

To thrive as a Machine Learning Co Op, you need strong programming skills (especially in Python), a solid foundation in mathematics and statistics, and coursework or experience in data science or machine learning. Familiarity with tools and frameworks like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is typically expected. Excellent problem-solving abilities, eagerness to learn, and effective communication help set you apart in collaborative and fast-paced environments. These skills and qualities are crucial for successfully contributing to real-world projects and advancing your expertise in the field.
What cities are hiring for Machine Learning Co Op jobs? Cities with the most Machine Learning Co Op job openings:
What are the most commonly searched types of Machine Learning jobs? The most popular types of Machine Learning jobs are:
What states have the most Machine Learning Co Op jobs? States with the most job openings for Machine Learning Co Op jobs include:
Machine Learning Co Op jobs near you
Machine Learning Co-Op (Fall 2026)

Machine Learning Co-Op (Fall 2026)

Hendrickson

Canton, OH • On-site

Full-time

Posted 2 days ago

Hendrickson rating

7.5

Company rating: 7.5 out of 10

Based on 35 frontline employees who took The Breakroom Quiz

207th of 417 rated machine equipment manufacturers

Job description

Job Summary:
Hendrickson is seeking a Machine Learning Co-Op for Fall 2026. The role involves partnering with stakeholders to define problems and deliver datasets, analyses, and ML prototypes while maintaining data quality and documentation standards.
Responsibilities:
• Partner with stakeholders to define problems, requirements, and success metrics (KPIs).
• Deliver reliable datasets, analyses, dashboards, and ML prototypes that address those needs.
• Communicate progress, risks, and results clearly to technical and non-technical audiences.
• Maintain data quality, documentation, and reproducibility standards.
• Run discovery (interviews, process mapping) and translate findings into clear requirements.
• Build and maintain clean datasets with SQL/Python; create visuals/dashboards (e.g., Power BI).
• Prototype and evaluate predictive/time-series models; document methods and results.
• Demo work, gather feedback, iterate, and prepare simple handoffs for reuse.
• Perform other duties as assigned.
Qualifications:
Required:
• Working toward a bachelor's degree in a major related to machine learning (e.g. computer science, statistics, mathematics, engineering, or a closely related field).
• Strong communicator and facilitator; comfortable writing clear docs.
• Familiar with Python and SQL; solid grasp of basic statistics and model evaluation.
• Organized, curious, and able to manage multiple projects and deadlines.
Preferred:
• Experience with time-series/forecasting, Power BI/DAX, or introductory deep learning/LLMs.
• Familiarity with version control (Git/GitHub) and basic cloud data tools.
Company:
Hendrickson is a designer and manufacturer of suspension systems and components for heavy-duty trucks. Founded in 1913, the company is headquartered in Itasca, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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