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Machine Learning Co Op Jobs in Texas (NOW HIRING)

Skyworks

Co-Op

Austin, TX · On-site

$22.50 - $42/hr

Job Title: Co-Op Posting Start Date: 11/13/25 Job Location(s): Austin If you are looking for a ... Create lessons learning document and proposing TO guidelines Required Experience and Skills

flowcontrol

Service Technician Co-Op

Tomball, TX · On-site

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

flowcontrol

Service Technician Co-Op

Tomball, TX

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

flowcontrol

Service Technician Co-Op

Tomball, TX · On-site

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

Howmet

Human Resources CO-OP Student

Wichita Falls, TX · On-site

$19/hr

Our CO-OP program offers structured hands-on training involving plant tours, lunch & learn seminars ... Our vacuum melted superalloys, machining, performance coatings and hot isostatic pressing for high ...

ONEOK

Engineering Co-op

Dallas, TX · On-site

$16.50 - $21.50/hr

JOB SUMMARY Join our dynamic team as an Engineering Co-op! This role is designed for current ... Gain practical engineering and project management experience through diverse learning rotations led ...

Enpro

QHSE Co-op- 1 year Program

Houston, TX · On-site

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 ...

Abbott

2026 Summer Engineering Co-Op

Plano, TX

$16.45 - $32.85/hr

Co-op-Typically a 6- to 8-month, full-time assignment * Each year, Abbott has Co-ops on assignment ... Students receive learning experiences and meaningful work that challenge and reward, working on ...

Abbott

2026 Summer Engineering Co-Op

Plano, TX · On-site

$16.45 - $32.85/hr

Co-op-Typically a 6- to 8-month, full-time assignment * Each year, Abbott has Co-ops on assignment ... Students receive learning experiences and meaningful work that challenge and reward, working on ...

Nokia

Customer Engineering Co-Op

Coppell, TX · Hybrid

$16.50 - $21.50/hr

A learning environment that fosters both personal growth and professional development - for your ... Experience working with Linux or virtual machine environments. * Contribute to lab setups by ...

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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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$53

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

As of Jun 11, 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.

Which 3 jobs will survive AI?

Machine Learning Co-ops are likely to find that roles requiring complex problem-solving, creativity, and emotional intelligence—such as data scientists, AI ethics specialists, and human-centered design professionals—will persist alongside AI advancements. These jobs involve tasks that are difficult for AI to fully replicate and often require interdisciplinary skills and critical thinking.

Which 5 jobs will survive AI?

Machine Learning Co-ops are likely to continue working in roles that require complex problem-solving, creativity, and human judgment, such as data analysis, AI system development, and research. Jobs that involve interpersonal skills, strategic decision-making, and tasks requiring emotional intelligence are also less susceptible to automation. Skills in critical thinking, domain expertise, and adaptability will help professionals remain relevant as AI advances.

Is ML a high paying job?

Machine Learning Co-ops are typically paid internships that offer competitive hourly wages or stipends, which can vary based on location, education level, and company size. Entry-level roles in machine learning often have higher starting salaries compared to many other tech internships, and full-time positions in the field tend to have above-average salaries due to the specialized skills required, such as programming in Python and experience with frameworks like TensorFlow or PyTorch.

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 is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or executive positions, often requiring advanced skills, extensive experience, and sometimes equity or bonuses. These roles are usually found in large tech companies or specialized AI firms and may involve leadership, strategic planning, and cutting-edge research.
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

QHSE Co-op- 1 year Program

Enpro Industries

Houston, TX • On-site

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 16 days ago

Job description

QHSE Co-op- 1 year Program
Job Title: Quality, Health Safety and Environmental Co-op
Location: Houston, TX
Duration: 1 Year (2026 - 2027)
Department: Manufacturing / Operations
Reports To: Plant Manager
Position Summary
The QHSE Co-Op will support the integration of Quality and Safety as a core value of Excellence in a manufacturing facility producing metal gaskets and rubber molded wall penetration elements. This role is designed as a hands-on developmental assignment, providing exposure to AS9100, ISO 45001, and OSHA compliance, while contributing meaningful, audit-ready deliverables.
Garlock Houston has a solid quality foundation with dedicated QA and QC resources. The QHSE Co-Op will focus on building and strengthening safety programs, aligning them with established quality systems, and helping translate system requirements into practical, shop-floor-ready procedures.
Learning Objectives & Program Outcomes
By the end of the 1-year co-op, the individual will have:
  • Practical experience developing OSHA-compliant safety procedures
  • Direct participation in ISO 45001 system implementation
  • Exposure to AS9100 requirements and audit expectations
  • Hands-on involvement with root cause analysis, corrective actions, and risk assessment
  • Experience working cross-functionally with Production, Maintenance, Quality, and Leadership
  • A strong understanding of how safety and quality systems reinforce operational excellence

Key Responsibilities (Under Supervision)
1) OSHA & Safety Program Development
  1. Assist in developing and updating written OSHA safety programs, such as:
  2. Hazard Communication (HazCom / GHS)
  3. Lockout/Tagout (program documentation and machine-specific procedures)
  4. PPE hazard assessments and selection
  5. Machine guarding assessments and gap logs
  6. Incident and near-miss reporting procedures
  7. Help organize Safety Data Sheets (SDS) and chemical inventories.
  8. Support safety inspections, job safety analyses (JSA/JHA), and corrective action tracking.

2) ISO 45001 Support
  1. Support the build-out and documentation of ISO 45001 elements, including:
    1. Hazard identification and risk assessment registers
    2. Operational controls and standard work
    3. Worker participation and communication records
    4. Training and awareness documentation
    5. Help ensure documentation is structured, controlled, and audit-ready.

3) Integration with Quality (AS9100 & AS13100 Alignment)
  1. Partner with QA/QC to:
    1. Align safety events and near misses with corrective action processes.
    2. Participate in root cause analysis using structured problem-solving methods.
    3. Ensure safety-related controls are reflected in work instructions and training.
    4. Learn how AS9100 requirements interface with operations, training, and risk management.
    5. Supports QHSE systems with emphasis on AS13100A Human Factors by identifying error-contributing conditions, improving procedure clarity, supporting root cause analysis, and promoting a just culture focused on systemic improvement rather than individual fault. [MG1]

4) Training & Employee Engagement
  1. Assist with safety onboarding materials for new hires.
  2. Help coordinate and document toolbox talks, safety meetings, and refresher training.
  3. Support workforce engagement initiatives (near-miss reporting, Safety Action Teams, safety culture activities).

5) Audits, Metrics & Reporting
  1. Support internal audits (EHS and integrated systems).
  2. Track and report basic safety metrics, such as training completion, inspections completed, incidents, and corrective action status.
  3. Assist with management review inputs related to safety performance and improvement actions.

Required Qualifications
  • Actively pursuing a degree in Safety, Engineering, EHS, or related field (final year or graduate)
  • Strong interest in manufacturing safety, quality systems, and operational excellence
  • Ability to write clear procedures and organize technical documentation
  • Proficiency with Microsoft Office (Word, Excel, PowerPoint)
  • Willingness to spend time on the manufacturing floor in PPE
  • Strong communication skills and willingness to ask questions and learn

Preferred Qualifications
  • Previous internship, co-op, or manufacturing experience
  • Introductory coursework in OSHA, industrial safety, or quality systems
  • Familiarity with basic problem-solving tools (5-Why, Fishbone, PDCA)
  • Interest in long-term career path in EHS, Quality, or Operations Leadership

Mentorship & Support
  • Direct mentoring by the Plant Manager and Quality/EHS leadership
  • Structured exposure to audits, leadership reviews, and cross-functional decision-making
  • Regular feedback sessions and learning checkpoints
  • Opportunity to build a portfolio of real safety and quality deliverables

Why This Co-Op Matters
This co-op is not observational-it is impact-driven. The individual will help establish foundational safety systems while learning how strong quality and safety execution enables performance, compliance, and culture in a regulated manufacturing environment.
This role is ideal for a candidate who wants meaningful responsibility and long-term career development-not just a resume line.
Garlock is a subsidiary of Enpro, a leading industrial technology company focused on critical applications across many end-markets, including semiconductor, industrial process, commercial vehicle, sustainable power generation, aerospace, food and pharma, photonics and life sciences.
At Enpro, we believe that diversity drives innovation and inclusion fosters growth. We are committed to creating a workplace where everyone feels valued and respected. Our employment decisions are based on merit, qualifications, and business needs, without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, age, disability, genetic information, marital status, military service, or any other status protected by applicable law. If you require accommodation due to a disability at any time during the recruitment and/or assessment process, please contact Human Resources, and we will make all reasonable efforts to accommodate your request.
Enpro carefully considers a wide range of compensation factors including the background, education, training, and experience required, as well as geographic considerations such as cost of labor, and applicable local and state laws. These considerations can cause offered compensation to vary. Actual offers will be based on the individual candidate. Bonus, gainshare, and/or equity may be eligible for this position. Enpro offers a range of benefits including, but not limited to medical, dental, vision, life, 401(k) matching, and other supplemental insurance options.
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