Research Intern, Robotics Data & Real-to-Sim
WorldEngine AI San Francisco, CA, US
What they're looking for
- Develop real-to-sim workflows that turn real-world images, video, and sensor data into simulation-ready scenes, objects, and environments
- Build tools to process, align, and validate robotics data, including visual observations, 3D geometry, and robot trajectories
- Investigate how reconstruction fidelity, scene coverage, and physical properties affect the usefulness of reconstructed environments for robot learning
- Design experiments and benchmarks to compare reconstructed environments with real-world reference data and measure their impact on robot learning and task performance
- Work with engineers to turn research prototypes into reproducible data pipelines, datasets, and evaluation tools
The full posting
Published by WorldEngine AI. Original posting (opens in a new tab)
ABOUT THE ROLE
At WorldEngine, we’re building the data infrastructure for Physical AGI. Real-world experience is central to that effort: the scenes robots operate in, the objects they interact with, and the data that captures what happens.
As a Research Intern, you’ll investigate how real-world observations and robot interactions can be converted into high-quality datasets and simulation-ready environments. You’ll work closely with our engineering and research teams on 3D reconstruction, real-to-sim workflows, and experiments that measure how data and simulation quality affect robot learning and evaluation.
WHAT YOU'LL DO
- Develop real-to-sim workflows that turn real-world images, video, and sensor data into simulation-ready scenes, objects, and environments
- Build tools to process, align, and validate robotics data, including visual observations, 3D geometry, and robot trajectories
- Investigate how reconstruction fidelity, scene coverage, and physical properties affect the usefulness of reconstructed environments for robot learning
- Design experiments and benchmarks to compare reconstructed environments with real-world reference data and measure their impact on robot learning and task performance
- Work with engineers to turn research prototypes into reproducible data pipelines, datasets, and evaluation tools
- Document methods, experiments, and findings, and contribute to technical reports or research publications where appropriate
WHAT WE'RE LOOKING FOR
- Currently pursuing a degree in computer science, robotics, electrical engineering, or a related field, or equivalent hands-on research experience
- Strong Python programming skills and experience implementing and testing machine learning or computer vision methods
- A foundation in 3D geometry, computer vision, or robot learning, with the ability to turn research ideas into working prototypes
- Comfortable working with imperfect real-world data, debugging pipelines, and designing clear, controlled experiments
- Clear technical communication and the ability to take ownership of a scoped research project in an early-stage team
NICE TO HAVE
- Research or project experience in 3D reconstruction, neural rendering, or scene understanding
- Experience with robotics simulators or tools for scene and asset generation
- Hands-on experience training or evaluating robot policies in simulation or on physical systems
- Experience building reproducible experiments, processing multimodal datasets, or contributing to open-source projects
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