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Machine Learning Co Op Jobs in Texas (NOW HIRING)

Nokia

Lab Engineer Co-op

Coppell, TX · Hybrid

Lab Engineer Co-op Duration : 4 months Date : September - December Location : Dallas, TX ... A learning environment that fosters both personal growth and professional development - for your ...

Heartland Co-op

Location Manager III

Farwell, TX · On-site

... Co-op by performing the following duties personally or through subordinate employees. Essential ... Develops plans for efficient use of materials, machines, and employees. * Reviews expenses and ...

Heartland Co-op

Location Manager III

Farwell, TX · On-site

... Co-op by performing the following duties personally or through subordinate employees. Essential ... Develops plans for efficient use of materials, machines, and employees. * Reviews expenses and ...

Nokia

Legal Co-op

Coppell, TX · Hybrid

A learning environment that fosters both personal growth and professional development - for your role and beyond Disclaimer for US/Canada Nokia maintains broad annual base salary ranges for its roles ...

ONEOK

NGGP Engineering Co-op

Dallas, TX · On-site

$16.50 - $21.50/hr

Gain practical engineering and project management experience through diverse learning rotations led ... co-workers, internal and external customers Ability to: utilize Microsoft Office applications ...

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All JobsMachine Learning Co Op JobsMachine Learning Co Op Jobs in Texas

Machine Learning Co Op information

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

As of Jul 16, 2026, the average hourly pay for machine learning co op in Texas is $20.88, according to ZipRecruiter salary data. Most workers in this role earn between $13.22 and $24.28 per hour, 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 are the most commonly searched types of Machine Learning jobs in Texas? The most popular types of Machine Learning jobs in Texas are:
What cities in Texas are hiring for Machine Learning Co Op jobs? Cities in Texas with the most Machine Learning Co Op job openings:
Machine Learning Co Op jobs near you
Seasonal Part Time Sales Associate

Seasonal Part Time Sales Associate

University Co-op

Austin, TX

$13.50 - $15.75/hr

Part-time

Re-posted 10 days ago

Job description

Seasonal Part Time Sales Associate

Position Summary
The Seasonal Part Time Sales Associate role is a non-exempt part time role reporting to the Assistant Store Director of Store Development. The Seasonal Part Time sales associate must align with our core values and provide great Co-op Land customer service to all our guests. In addition to providing great customer service, this role is responsible for maintaining sales floor merchandising standards and cleanliness as well as efficiently and effectively executing all operational tasks. Every role at the Co-op contributes to supporting students through our course material scholarship program.
Key Competencies for Success:
Customer Focus, Collaborating With Others, Attention to Detail, Initiative, Adaptability, Cash Handling, Continuous Learning, Problem Solving
Key Accountabilities amp; Achievements:
  • Customer Service
    • Welcome, greet, and support customers throughout their shopping experience.
    • Guide customers to the products and offer recommendations.
    • Offer baskets to support customers' shopping experience.
    • Make recommendations to customers.
    • Share information about our Not-for-Profit mission and course material scholarship initiative.
  • Floor Recovery
  • Ensure that all merchandise is sized and organized on the sales floor.
  • Fold product to merchandising standards.
  • Ensure all products are in their designated area on the sales floor during store hours.
  • Maintain overall sales floor cleanliness during store hours.
Product Flow
  • Maintain proper inventory levels of sales floor merchandise.
  • Support timely receiving and processing of shipments.
  • Accurately and efficiently fulfill web orders.
Knowledge, Abilities amp; Experience for Success:
  • High School Diploma or GED is required.
  • Communication skills
  • Customer-focused mindset to provide outstanding customer service to all guests.
  • Ability to multitask and pivot during lively business events to ensure a great shopping experience.
  • Retail technology savvy.
  • Passionate about the University of Texas
Physical Demands:
  • Ascending or descending ladders, stairs, ramps and the like.
  • Remaining in a stationary position, often standing for prolonged periods
  • Moving about to accomplish tasks or moving from one sales floor to another
  • Adjusting or moving objects up to 50 pounds in all directions
  • Repeating motions that may include the wrists, hands and or/fingers
Work Environment:
  • Ability to work a varying retail schedule including early mornings, evenings, weekends, holidays and game days.
  • Well-lighted, heated and/or air-conditioned indoor retail setting with adequate ventilation.
  • Moderate noise (examples: customer and employee conversation, store music, light traffic).
Please see our career site to learn about our culture and values. Please note that this role profile is not intended to provide an exhaustive list of competencies, accountabilities, and achievements required of the team member in this role.
Our commitment to equal opportunity employment (EOE) extends to all aspects of the employment relationship, including recruitment, hiring, promotion, transfer, disciplinary action, layoff, training, and benefits. We strive to provide a work environment free from discrimination, harassment, and retaliation.

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