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Fall Machine Learning Co Op Jobs in Houston, TX (NOW HIRING)

Our capabilities-including ERP systems, 3D CAD design, and on-site manual and CNC machining-allow ... Available to begin the co-op assignment in Fall 2026 Preferred Qualifications * Previous ...

New

Our capabilities--including ERP systems, 3D CAD design, and on-site manual and CNC machining--allow ... Available to begin the co-op assignment in Fall 2026 Preferred Qualifications * Previous ...

New

Fall 2026 (August-December) * Location: Conroe, TX * Work Environment: Onsite * Hours: Full-time for the duration of your co-op What You'll Do as an Engineering Co-op * Develop fixture designs to ...

Support warehouse and parts handling when required Learning Objectives By the end of the co-op, participants will gain exposure to: * Fundamentals of compressed air systems and applications

Support warehouse and parts handling when required Learning Objectives By the end of the co-op, participants will gain exposure to: * Fundamentals of compressed air systems and applications

Support warehouse and parts handling when required Learning Objectives By the end of the co-op, participants will gain exposure to: * Fundamentals of compressed air systems and applications

Learning Objectives & Program Outcomes By the end of the 1‑year co‑op, the individual will have ... Machine guarding assessments and gap logs * Incident and near‑miss reporting procedures * Help ...

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Fall Machine Learning Co Op information

See Houston, TX salary details

$24.4K

$40.7K

$84K

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

As of Aug 14, 2026, the average yearly pay for fall machine learning co op in Houston, TX is $40,666.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,000.00 and $43,900.00 per year, depending on experience, location, and employer.

What is a Fall Machine Learning Co Op?

A Fall Machine Learning Co-Op is a temporary, typically full-time position for students or recent graduates to gain hands-on experience in applying machine learning techniques. These roles usually involve working with data, training models, and optimizing algorithms under the supervision of experienced engineers or researchers. They are offered during the fall semester and can last several months. Companies use these positions to provide practical learning opportunities and assess potential future hires.

What can I expect from the day-to-day experience of a Fall Machine Learning Co Op?

As a Fall Machine Learning Co Op, you'll typically work with a team of data scientists and engineers on real projects that may involve data cleaning, model development, testing, and reporting insights. Your days might include collaborating in meetings, coding, analyzing data, and presenting findings to team members or supervisors. You'll receive mentorship from experienced professionals and have opportunities to participate in code reviews and brainstorming sessions. This structure helps you build technical skills, broaden your professional network, and gain a comprehensive understanding of how machine learning is applied in a business setting.

What are the key skills and qualifications needed to thrive in the Fall Machine Learning Co Op position, and why are they important?

To thrive as a Fall Machine Learning Co Op, you should have a solid background in programming (especially Python), statistics, and machine learning concepts, often supported by coursework or hands-on projects in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, and data analysis libraries such as pandas and scikit-learn is highly valued, while certifications in AI or data science can be a plus. Strong problem-solving skills, eagerness to learn, effective communication, and teamwork help you stand out in this role. These skills are crucial for contributing to real-world projects, collaborating with technical teams, and gaining valuable experience in a fast-paced, innovation-driven environment.

What are popular job titles related to Fall Machine Learning Co Op jobs in Houston, TX?

For Fall Machine Learning Co Op jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching Fall Machine Learning Co Op jobs in Houston, TX look for?

The top searched job categories for Fall Machine Learning Co Op jobs in Houston, TX are:

What cities near Houston, TX are hiring for Fall Machine Learning Co Op jobs?

Cities near Houston, TX with the most Fall Machine Learning Co Op job openings:

Infographic showing various Fall Machine Learning Co Op job openings in Houston, TX as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $40,666 per year, or $19.6 per hour.

Mechanical Engineer Co-Op

Welker, Inc

Sugar Land, TX • On-site

$17 - $23/hr

Part-time

Posted yesterday

New


Job description

About Welker
At Welker, our mission is to Build Something Greater. We are a family-owned manufacturing company based in Sugar Land, Texas, with over 70 years of experience designing innovative solutions for the oil and gas industry.
Our capabilities-including ERP systems, 3D CAD design, and on-site manual and CNC machining-allow us to provide complete, high-quality products and turnkey solutions to customers worldwide.
If you're looking to make an impact at a stable, forward-thinking company where your work is tangible and valued, Welker may be the right fit.
About the Role
We are seeking a Mechanical Engineer Co-op to support our engineering team in the design and development of innovative mechanical equipment and customer-specific solutions.
This hands-on co-op opportunity provides meaningful engineering experience through direct involvement in product design, engineering analysis, and manufacturing support. You'll work alongside experienced engineers to develop practical solutions, contribute to real customer projects, and gain exposure to the full product lifecycle from concept through production.
Key Responsibilities
  • Analyze customer specifications and assist in developing solutions that meet customer requirements and industry standards
  • Support Engineering department projects and complete assignments within established deadlines
  • Collaborate with Drafting, Sales, and Estimating teams to support customer projects and work cross-functionally with Research & Development, Manufacturing, and Quality Control teams
  • Assist in performing design and safety calculations
  • Support Engineering documentation

Required Qualifications
  • Current Junior or Senior pursuing a bachelor's degree in mechanical engineering from an ABET-accredited university
  • Working knowledge of SolidWorks
  • Proficiency with Microsoft Office applications
  • Ability to quickly adapt to new software programs including the Welker ERP software
  • Familiarity with mechanical design principles and engineering fundamentals
  • Strong verbal and written communication skills
  • Excellent organizational skills and attention to detail
  • Available to begin the co-op assignment in Fall 2026

Preferred Qualifications
  • Previous engineering internship, co-op, research, or project experience
  • Experience creating engineering drawings and 3D models
  • Familiarity with manufacturing processes and machining concepts
  • Strong interest in product design, manufacturing, and industrial equipment
  • Demonstrated ability to work independently and as part of a collaborative team

Why Join Welker?
  • Work on real, built products from concept to production
  • Be part of a collaborative, cross-functional engineering team
  • Gain exposure to both legacy product improvements and new product development
  • Join a stable, family-owned company with long-term growth

Additional Requirements
  • Must be authorized to work in the U.S.
  • Must successfully complete a drug screen, physical, and background check

Apply Today
If you're ready to design impactful products and see your work come to life, we'd love to hear from you.
Learn more: https://www.welker.com/