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Internship Graduate Machine Learning Jobs in Houston, TX

Fervo Energy

Data Science Internship

Houston, TX

Description Internship Overview You won't be running coffee orders or shuffling paperwork this ... Support development of machine learning models for real-world business problems * Communicate ...

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Internship Graduate Machine Learning information

See Houston, TX salary details

$24.4K

$40.7K

$84K

How much do internship graduate machine learning jobs pay per year?

As of Sep 14, 2026, the average yearly pay for internship graduate machine learning 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 an internship graduate machine learning?

Internship Graduate Machine Learning positions are entry-level roles designed for recent graduates or students who have completed coursework in machine learning, data science, or related fields. These internships provide hands-on experience working with real-world data, building and testing machine learning models, and collaborating with experienced professionals. Interns gain exposure to industry-standard tools and techniques, helping them bridge the gap between academic learning and practical application. Such positions are valuable for building a portfolio, networking, and enhancing job prospects in the rapidly growing field of artificial intelligence.

What types of projects do internship graduate machine learning roles typically involve, and how are responsibilities structured within the team?

Internship Graduate Machine Learning roles often focus on supporting ongoing research or development projects, such as building predictive models, cleaning and analyzing data, or prototyping algorithms. Interns usually collaborate closely with data scientists and engineers, contributing to specific project milestones while learning best practices in model development and deployment. Responsibilities are often structured to allow for mentorship and feedback, with interns participating in regular team meetings, code reviews, and brainstorming sessions. This collaborative environment provides valuable exposure to real-world machine learning workflows and helps interns build both technical and soft skills relevant to the field.

What are the key skills and qualifications needed to thrive as an internship graduate machine learning, and why are they important?

To thrive as an Internship Graduate in Machine Learning, you typically need a strong background in mathematics, programming (especially Python), and familiarity with algorithms and data structures, often supported by coursework or a degree in computer science, statistics, or a related field. Hands-on experience with machine learning frameworks like TensorFlow or PyTorch, and knowledge of tools such as Jupyter Notebooks and version control systems like Git, are highly valued. Curiosity, problem-solving, teamwork, and effective communication are crucial soft skills to excel in collaborative and innovative environments. These competencies enable interns to contribute to real-world projects, adapt to fast-changing technologies, and communicate findings clearly within interdisciplinary teams.

What is the difference between Internship Graduate Machine Learning vs Data Analyst?

AspectInternship Graduate Machine LearningData Analyst
Required CredentialsDegree in Computer Science, Data Science, or related field; basic knowledge of programming and statisticsDegree in Statistics, Mathematics, or related field; proficiency in data visualization and analysis tools
Work EnvironmentTech companies, research labs, startups; project-based, collaborative teamsBusiness, finance, marketing sectors; focus on reporting and data interpretation
Employer & Industry UsageUsed in tech, AI, and research industries for developing machine learning modelsCommon in corporate, finance, and consulting firms for data-driven decision making

While both roles involve working with data, an Internship Graduate Machine Learning focuses on developing algorithms and models using programming skills, often in tech environments. In contrast, a Data Analyst emphasizes interpreting data, creating reports, and supporting business decisions. The roles overlap in data handling but differ in technical depth and application focus.

Internship Graduate Machine Learning jobs near you
Infographic showing various Internship Graduate Machine Learning 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.

AI Applications Engineering Internship

Houston, TX • On-site

Fervo Energy Company
Clean Energy Semiconductors Manufacturing • 11 - 50 employees
Learn more about Fervo Energy Companyexternal

$16 - $20.75/hr

Internship

Posted 14 days ago

Job description

Job Type
Internship
Description
Internship Overview
You won't be running coffee orders or shuffling paperwork this summer. At Fervo, interns are handed something real: a project of your own, scoped with your manager on day one and yours to drive for the full 12 weeks. You'll work side-by-side with the teams building the next generation of geothermal energy, tackling problems that genuinely move the business forward. At the end of the summer, you'll present your work to our executive leadership team, department leads, and fellow interns, sharing real results with a real audience. This is a real seat at the table - and a real shot at what comes next.
Position Description
Fervo Energy is developing next-generation geothermal power to deliver firm, carbon-free energy at scale, anchored by our flagship Cape Station project in Milford, Utah. We're building a dedicated AI team to unlock transformational value across drilling, reservoir modeling, operations, and commercial strategy, and we're looking for a graduate-level AI Applications Engineering Intern (PhD candidates strongly preferred) to help lead the way.
You'll apply cutting-edge AI to real problems in geothermal development, from hybrid AI-physics models for subsurface forecasting to RAG systems for knowledge management and predictive maintenance models, serving as an internal consultant on Fervo's Strategy Team and partnering with end-user departments to guide decision-makers through complex technical, operational, and commercial challenges
Requirements
Responsibilities
  • Develop, train, and evaluate advanced AI models (LLMs, ML, time-series, hybrid physics-informed)
  • Collaborate with end-user teams to scope and deliver applied AI solutions
  • Contribute to Fervo's centralized AI infrastructure and data architecture
  • Document methodologies and provide clear technical communication to technical and non-technical stakeholders
  • Present findings and recommendations to cross-functional teams, including senior leadership

Required Qualifications
  • Graduate student or PhD candidate in Computer Science, Applied Mathematics, or a related quantitative field with a focus on AI/ML
  • Strong proficiency in Python and machine learning frameworks (e.g., PyTorch, TensorFlow, Scikit-learn)
  • Demonstrated research experience in one or more of: large language models, time-series analysis, physics-informed ML, optimization, or reinforcement learning
  • Ability to apply theoretical knowledge to practical, messy, real-world datasets
  • Excellent problem-solving, communication and collaboration skills
  • Self-starter with the ability to scope and drive projects independently

Preferred Qualifications
  • Experience with energy systems, industrial operations, or geoscience applications
  • Prior experience with RAG architectures, data engineering, or scalable model deployment

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