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Machine Learning Co Op Jobs in Texas (NOW HIRING)

Nokia

IODT Automation Co-op

Coppell, TX · On-site

IODT Automation Co-op Duration: 4 to 8 months Date: September 8 - December 18, 2026 Location ... A learning environment that fosters both personal growth and professional development - for your ...

Persona AI

Software Engineering Intern

Houston, TX

... machine learning, or computer vision (through classes or personal interest) * Familiarity with version control systems (Git) or software development practices * Previous internship, co-op, or project ...

University Co-op

Seasonal Part Time Sales Associate

Austin, TX · On-site

$13.50 - $15.75/hr

Every role at the Co-op contributes to supporting students through our course material scholarship ... Continuous Learning, Problem Solving Key Accountabilities & Achievements: * Customer Service

Nokia

Lab Engineer Co-op

Coppell, TX · On-site

$20.10 - $70.40/hr

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 ...

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 ...

New

Nokia

Legal Co-op

Coppell, TX · On-site

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 ...

Heartland Co-op

Location Manager III

Farwell, TX

... 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 ...

New

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 ...

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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 Jun 12, 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
Junior AI/ML Engineer (Data & Cloud Platforms)

Junior AI/ML Engineer (Data & Cloud Platforms)

Mod Op

Dallas, TX • On-site

$113K - $136K/yr

Full-time

Posted 8 days ago

Job description

About Mod Op
Mod Op is a full-service advertising agency able to offer clients a full suite of solutions. Mod Op can offer you access to low-cost, high-quality health care options and a team of enthusiastic, collaborative and motivated coworkers who see career development and personal development as intertwined.
At Mod Op, we're more than just an agency-we're a team of forward-thinking professionals who are passionate about driving client success. We believe in fostering meaningful relationships, collaborating across disciplines, and delivering impactful solutions that help businesses grow. If you are a strategic thinker with a passion for building lasting client partnerships, we'd love to hear from you. Join us and be part of a company that values innovation, creativity, and excellence in everything we do.
About the role
As a Junior AI/ML Engineer (Data & Cloud Platforms) with 1-2 years of experience, you will support the development of scalable data systems and contribute to AI and machine learning initiatives. This role combines data engineering, cloud technologies, and machine learning implementation to help build intelligent data-driven solutions.
You will work with AWS, GCP, and Azure cloud services, integrate with CRM and marketing platforms, and support analytics and AI solutions through tools such as Google Looker and Tableau. The role will involve working with both data pipelines and machine learning workflows to enable advanced analytics and automation.
The position operates under a hybrid work model, requiring in-office presence at the Dallas, Texas location two days per week, with the remaining days worked remotely.
What you'll do
Data Pipeline Development:
Assist in designing, developing, and maintaining scalable ETL/ELT pipelines across cloud platforms such as GCP, AWS, and Azure, using services like Dataflow, Cloud Composer (Airflow), Azure Synapse, and AWS Data Pipelines.
Data Integration:
Work with structured and unstructured data sources, including CRM systems, marketing platforms, APIs, and internal business systems, to support analytics and AI-driven applications.
Database Management:
Develop and optimize queries for SQL and NoSQL databases such as Teradata, BigQuery, Cassandra, and cloud data warehouses.
Machine Learning Implementation:
Support the development and deployment of machine learning models using Python and data science libraries (Pandas, NumPy, Scikit-learn) and cloud AI services such as GCP Vertex AI, AWS SageMaker, or Azure ML.
AI-Enabled Data Workflows:
Assist in building data pipelines that support predictive analytics, automation, and AI-driven insights.
Data Visualization:
Build and maintain dashboards using Google Looker and Tableau to help business and marketing teams understand and act on data insights.
Collaboration:
Work closely with data engineers, analysts, data scientists, and marketing teams to understand business requirements and support the development of data and AI solutions.
Required Qualifications
Cloud Platforms:
Hands-on experience with GCP, AWS, or Azure, particularly in data engineering or machine learning environments.
Programming Skills:
Strong proficiency in Python with experience using data processing and machine learning libraries such as Pandas, NumPy, and Scikit-learn.
Database Experience:
Experience working with SQL and NoSQL databases, including platforms such as BigQuery, Teradata, Cassandra, or similar technologies.
Data Visualization:
Experience building dashboards and reports using Google Looker or Tableau.
Machine Learning Knowledge:
Basic understanding of machine learning workflows, model training, evaluation, and deployment in cloud environments.
Data Automation & Transformation:
Experience with Alteryx or similar tools for workflow automation and data preparation.
Preferred Qualifications
Experience with data warehousing platforms such as Snowflake or Redshift.
Exposure to Apache Spark, Airflow, or other orchestration tools.
Familiarity with MLOps practices and cloud-based ML platforms.
Understanding of data governance, security, and compliance practices.
Relevant certifications such as Google Cloud Professional Data Engineer or Machine Learning certifications.
Mod Op, LLC provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

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