Autonomy Software Engineering Internship, World Modeling

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Job Title

Autonomy Software Engineering Intern, World Modeling

Department

Robotics Software Engineering

Employment Type

Internship

Location

Houston, TX – Onsite

WHO WE ARE

Persona AI is building humanoid robots for the most demanding environments in heavy industry — shipyards, steel mills, fabrication facilities, and offshore platforms — performing welding, grinding, maintenance, inspection, and material-handling work that is dangerous, physically demanding, and increasingly difficult to staff.

We are backed by leading strategic and financial investors and engaged with global industrial leaders across Korea, Japan, the United States, and Singapore. Korea is the center of gravity for our early commercial strategy, anchored by relationships with the world’s leading shipbuilders and steelmakers. Our work spans both the robot platform itself and the systems, partners, and playbooks required to deploy it at scale.

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.

OUR INTERNSHIP PROGRAM

At Persona AI, our internship program gives you direct, hands-on experience building cutting-edge humanoid robotics alongside industry experts. We offer full-time term opportunities across three upcoming cohorts:

Fall 2026

August – December

Spring 2027

January – May

Summer 2027

May – August

As an intern, you’ll be paired 1:1 with a senior engineer mentor to accelerate your growth and guide your technical contributions. You will bond with your cohort through intern group lunches, gain cross-functional perspective during company-wide learning lunches, and unwind with fun team activities throughout the term. Whether you're working on advanced motion planning or real-world system testing, you'll tackle meaningful engineering challenges while immersing yourself in our collaborative startup culture.

Application Review Process

We evaluate applications as they are received rather than waiting for the posted deadline to pass. Positions for each cohort are filled on a first-come, first-served basis, and the portal will close as soon as all available roles are finalized.

To give yourself the best chance of securing a spot, keep these tips in mind:

Apply Early

Submitting your resume as soon as possible ensures your materials are reviewed before interview slots fill up.

Cohort Availability

Popular terms—especially Summer 2027—tend to reach capacity quickly.

Rolling Interviews

Interviews and candidate evaluations begin immediately upon application receipt.

Persona AI is an Equal Opportunity Employer.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, age, disability, veteran status, or any other characteristic protected by applicable federal, state, or local law.