Autonomy Software Engineering Internship, World Modeling

Public source summary from intern-list.com / Jobright.

Persona AI is building humanoid robots for demanding heavy-industry environments such as shipyards, steel mills, and fabrication facilities. The Autonomy Software Engineering Intern will help build the world-modeling layer of the autonomy stack by curating industrial video data, fine-tuning models, developing synthetic data and evaluation pipelines, and integrating autonomous behaviors for humanoid robots.

Responsibilities

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

Qualifications:

• 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
• 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

Benefits:

Paired 1:1 with a senior engineer mentor to accelerate your growth and guide your technical contributions.

Intern group lunches.

Company-wide learning lunches.

Fun team activities throughout the term.