Research Engineer, 3D & Multi-View Geometry

ABOUT THE TEAM Our Robotics team is focused on unlocking general-purpose robotics and pushing toward AGI-level intelligence in dynamic, real-world settings. Working across the full model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We aim to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve people’s lives.

ABOUT THE ROLE As a Research Engineer on the Robotics team, you will develop systems that enable robots to perceive, localize, and reconstruct the world in 3D from multi-camera and multimodal sensor data. You will work on real-time and offline perception pipelines used during teleoperation and robot data collection, as well as scalable systems for reconstructing and tracking 3D structure from large datasets. We’re looking for people who combine strong fundamentals in computer vision with practical experience building robust perception systems.

The ideal candidate is comfortable working across classical geometry-based approaches and modern machine learning methods, and enjoys collaborating closely with AI researchers and engineers. This role is based in San Francisco, CA. We use a hybrid work model of 4 days in the office per week and offer relocation assistance to new employees.

IN THIS ROLE, YOU WILL: - Develop and deploy real-time localization and scene understanding systems used during robotic data collection with multi-camera sensor stacks and teleoperation platforms. - Build systems for large-scale 3D reconstruction, point tracking, and scene alignment across massive datasets, enabling new approaches to world modeling and perception. - Work with research and engineering teams to scale multi-view geometry pipelines to large datasets.

• Improve the accuracy, robustness, and scalability of perception systems used in robotics data collection and training pipelines. - Collaborate across robotics, perception, and ML teams to integrate geometry-based methods with learned models. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have industry experience building real-time localization, 3D reconstruction, or visual perception systems in robotics, self-driving vehicles, AR/VR headsets, mapping, or other real-world environments.
• Have a deep understanding of multi-view geometry, camera calibration, bundle adjustment, feature tracking, structure-from-motion, and sources of error in real-world sensor systems. - Have experience with large-scale data processing pipelines or are excited to learn and work with infrastructure that supports large datasets. - Enjoy working in fast-moving environments and collaborating closely with engineers and researchers to ship systems quickly.

About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates.

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