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Machine Learning Co Op Jobs in Texas (NOW HIRING)

Optimum

Sr Machine Learning Engineer

Plano, TX · On-site

$97K - $134K/yr

Job Summary Machine Learning Engineers work to deploy end-to-end solutions to business problems ... Our employees are empowered to do the right thing for our customers and co-workers and to recognize ...

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 ...

Turner Construction

Intern - Dallas

Dallas, TX · On-site

$14.75 - $19.75/hr

Where applicable, your assignment will support learning that applies to earning educational credits. Essential Duties & Key Responsibilities:Depending on business need and location, the Intern/Co-Op ...

Turner Construction

Intern - Houston

Houston, TX · On-site

$14.25 - $19/hr

Where applicable, your assignment will support learning that applies to earning educational credits. Essential Duties & Key Responsibilities:Depending on business need and location, the Intern/Co-Op ...

Turner Construction

Intern - Austin

Austin, TX · On-site

$14.75 - $19.75/hr

Where applicable, your assignment will support learning that applies to earning educational credits. Essential Duties & Key Responsibilities:Depending on business need and location, the Intern/Co-Op ...

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Machine Learning Co Op information

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

As of Jun 13, 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
Sr Machine Learning Engineer

Sr Machine Learning Engineer

Optimum

Plano, TX • On-site

$97K - $134K/yr

Other

Posted 9 days ago

Optimum rating

7.3

Company rating: 7.3 out of 10

Based on 51 frontline employees who took The Breakroom Quiz

41st of 78 rated telecommunications companies

Job description

Are you looking to Optimize your life? Start your exciting path to a rewarding career today!

  
We are Optimum, a leader in the fast-paced world of connectivity, and we're seeking driven and enthusiastic professionals to join our team, empower lives, fuel businesses, and drive innovation. Connectivity is now longer a luxury, but a necessity. A career at Optimum means you'll be enabling progress and enhancing lives by providing reliable, high-speed connectivity solutions that keep the world connected. Our successes, now and in the future, are powered by our amazing product, a commitment to our people and culture, and the connections we make in our communities.


If you are resourceful, collaborative, and passionate about delivering consistent excellence, Optimum is for you! 

Job Summary

Machine Learning Engineers work to deploy end-to-end solutions to business problems leveraging AI and/or ML principles as needed to create those solutions. MLEs will take requests from stakeholders, define the components required for the project, gather data necessary for project EDA and training, then work with stakeholders to develop a plan around the productionized use of the solution, and work to put that solution into final production.

Responsibilities
  • Consult with stakeholders to gather business requirements, translate them into data solutions, design high-level model structures and demonstrate deep expertise in advanced analytics techniques (e.g., AI and ML) to design, prototype, and build solutions to business problems
  • Lead communication with other stakeholders to drive use case development and manage expectations on model limitations and lead times
  • Analyze data to identify useful relations, patterns and features that are predictive of user behaviors, preferences, intents, interests
  • Manage and execute entire projects from start to finish, including cross-functional project management; data collection and manipulation, analysis and modeling; communication of insights and recommendations; productionalization of final model products
  • Share findings with stakeholders to improve business decisions and/or influence strategic direction.
  • Monitor and stay updated with industry trends and emerging technologies to identify opportunities for innovation and improvement
  • Developing and maintaining the end to end modeling code and standardizing the code for reusability in the production environment.
  • Profiling users including customer segmentation to help the marketing team to target specific audience for upgrading to services and also for the user retention
Qualifications
  • Degree in a quantitative discipline, such as Data Science, Applied Mathematics, Statistics, Economics, Operations Research, Computer Science, Mathematics, Physics, Biology, Chemistry or Engineering. An advanced degree, Data Science bootcamp or MOOC certification is a plus.
  • 3-5 years of work experience in classification, regression, clustering, natural language processing NLP, experiments, and optimization.
  • Ability to apply Bayesian inference, frequentist statistics, causal modeling, and / or machine learning techniques.
  • Experience with any of these: customer segmentation, campaign targeting and effectiveness, A/B experiments, quasi-experiments, sales forecasting, churn propensity modeling, customer lifetime value analysis, credit risk, geospatial analytics, survey key-drivers, marketing mix modeling, multi-touch attribution, or recommender systems.
  • Highly skilled in R and Python for statistical and machine learning programming.
  • Highly skilled in SQL & Python coding to wrangle and explore structured & unstructured data.
  • Proficient with server or Cloud computing platforms, such as Google Compute Engine or EC2.
  • Proficient with data warehouses, such as Oracle, Big Query, or AWS.
  • Subject matter scientist that can review the literature to identify state of the art solutions to a business problem.

At Optimum, every action and interaction we take part in, is driven by our three Guiding Principles: Do What's Right, Drive One Optimum, and Make It Happen. These aren't just words, they help us build trust, create real community, and embrace new ways of thinking. Our employees are empowered to do the right thing for our customers and co-workers and to recognize and reward these behaviors when we see them. It's all part of the bigger picture of "Be The Difference" where each employee knows they have the power to enact real change, share new ideas, and understand that learning never stop.

If you have the drive to succeed and are ready to embark on a thrilling career, seize this opportunity today, and join our winning team. Together, we'll shape the future of connectivity.

All job descriptions and required skills, qualifications and responsibilities for a particular position are subject to modification by the Company from time to time, in the Company's discretion based on business necessity.

We are an Equal Opportunity Employer committed to recruiting, hiring and promoting qualified people of all backgrounds regardless of gender, race, color, creed, national origin, religion, age, marital status, pregnancy, physical or mental disability, sexual orientation, gender identity, military or veteran status, or any other basis protected by federal, state, or local law.

The Company collects personal information about its applicants for employment that may include personal identifiers, professional or employment related information, photos, education information and/or protected classifications under federal and state law. This information is collected for employment purposes, including identification, work authorization, FCRA-compliant background screening, human resource administration and compliance with federal, state and local law.

Applicants for employment with The Company will never be asked to provide money (even if reimbursable) as part of the job application or hiring process. Please review our Fraud FAQ for further details.

 
Pay is competitive and based on a number of job-related factors, including skills and experience. The starting pay rate/range at time of hire for this position in New York is $156,774.00 - $198,273.00 / year. The starting pay rate/range at time of hire for this position in Plano, Texas is $130,645.00 - $165,228.00 / year. For other locations, please inquire with your recruiter. The rates/ranges provided herein are the anticipated pay at the time of hire, and do not reflect future job opportunity.

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