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Internship Graduate Machine Learning Jobs in Houston, TX

Junior, Senior, or Graduate Student * Expected graduation date: Fall 2027 through Spring 2029 * A minimum of ten (10) continuous weeks availability for internship Preferred: * A minimum cumulative ...

Interns will be provided guidance by a supervisor and a technical mentor. We encourage the ... Practical experience with geoscience coding, data science, and/or machine learning. Why Intern at ...

... machine learning research applications. * Curriculum Awareness & Adaptive Instruction: Familiar ... graduate statistics curricula and common challenges such as understanding measure-theoretic ...

... learning experiences within our programs and communities. We offer placements across eleven cities ... Applicable Degree Programs We welcome students pursuing a variety of undergraduate and graduate ...

Internship

Houston, TX ยท On-site

... learning experiences within our programs and communities. We offer placements across eleven cities ... Applicable Degree Programs We welcome students pursuing a variety of undergraduate and graduate ...

Internship

Houston, TX ยท On-site

... learning important professional skills while serving some of the most vulnerable members of our ... General Internship Application Process Opportunities are available for graduate students attending ...

... learning experiences within our programs and communities. We offer placements across eleven cities ... Applicable Degree Programs We welcome students pursuing a variety of undergraduate and graduate ...

Showing results 21-40

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 Aug 7, 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 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.

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 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 popular job titles related to Internship Graduate Machine Learning jobs in Houston, TX? For Internship Graduate Machine Learning jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Internship Graduate Machine Learning jobs in Houston, TX look for? The top searched job categories for Internship Graduate Machine Learning jobs in Houston, TX are:
What cities near Houston, TX are hiring for Internship Graduate Machine Learning jobs? Cities near Houston, TX with the most Internship Graduate Machine Learning job openings:
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.

Autonomy Software Engineering Internship, World Modeling

Persona AI

Houston, TX โ€ข On-site

Full-time

Posted 3 days ago

New


Job description

Job Title: Autonomy Software Engineering Intern, World Modeling
Department: Robotics Software Engineering
Employment Type: Internship, Fall 2026
FLSA: Exempt
Location: Houston, TX - Onsite
Persona AI is developing and commercializing rugged, multi-purpose humanoid robots that perform real work. Persona's founding team has a decades-long history in humanoid robotics, bionics, and product development delivering robust hardware that has touched the stars, worked miles below the surface of the ocean, and even roamed Disney Parks. Our mission is focused squarely on shipping beautiful, reliable products at massive scale, while building a customer-focused team to achieve these aims.
We're looking for an Autonomy Software Engineering Intern to help build the world modeling layer of our autonomy stack. You will work hands-on with NVIDIA Cosmos3, curating real-world industrial video data from our customer facilities and fine-tuning models to give our humanoid robots a grounded understanding of the environments they operate in.
This is a paid summer internship based in Houston, TX. You will report to the Behavior Coordination Lead and work directly with the autonomy team alongside our machine learning, perception, and simulation engineers.
Your Role
  • Design and implement autonomy and behavior coordination algorithms for an industrial humanoid platform
  • Work with manipulation, locomotion, and perception engineers to integrate robot skills into autonomous robot behaviors
  • Implement data curation pipelines that enable our robots to understand a variety of real-world industrial tasks.
  • Develop synthetic data generation pipelines for post-training of humanoid world models
  • Design and implement pipelines for autonomous behavior evaluation, benchmarking, and regression testing
  • Turn raw industrial video footage (shipyards, steel fabrication, welding cells) into structured, high-quality training data.
  • Design and evaluate reasoning benchmarks that measure how well a fine-tuned world model grounds language queries in real shipyard and fabrication-plant scenes.
We're Looking For
  • Currently pursuing a BS, MS, or PhD in Robotics, Computer Science, Machine Learning, Electrical Engineering, or a related field; recent graduates are also welcome.
  • Hands-on experience training, fine-tuning, or evaluating modern deep learning models in PyTorch.
  • Strong Python skills; comfortable writing data processing scripts, training loops, and evaluation harnesses.
  • Working familiarity with at least one vision-language model, large language model, or video understanding model.
  • Practical experience building data pipelines: ingestion, filtering, labeling workflows, deduplication, train/val/test splits.
  • Comfortable working in Linux environments with Git, containers (Docker), and cloud GPU infrastructure.
  • Self-directed and able to make steady progress on an open-ended research problem with weekly check-ins rather than daily direction.
Preferred or Bonus Qualifications
  • Direct experience with NVIDIA Cosmos or comparable world foundation models.
  • Exposure to NVIDIA Isaac Sim, Omniverse, or OpenUSD for synthetic data generation and scene variability.
  • Familiarity with humanoid or mobile-manipulator robotics, ROS/ROS 2, and the broader autonomy stack.
  • Experience with motion capture data, egocentric video capture, or first-person dataset construction.
  • Exposure to behavior trees, task and motion planning, or LLM-driven planning architectures.
  • Familiarity with NVIDIA Isaac Lab, NIM microservices, or the Hugging Face training ecosystem.
  • Prior internship, research, or open-source work on physical AI, embodied reasoning, or robot learning.
Why join Persona AI?
  • You'll work on technology that's redefining the possibilities of robotics and human interaction.
  • Work alongside passionate teammates who value diversity, creativity, and continuous learning.
  • Enjoy full access to advanced prototyping tools, labs, and the freedom to experiment and innovate.
  • We offer competitive intern compensation, a flexible work environment, and meaningful technical mentorship.

Persona AI embraces diversity and equal opportunity in a serious way. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better our work will be.