Responsibilities

• Design and conduct original research in computer vision, generative 3D, and robotics learning, formulating hypotheses and running experiments to prove or disprove outcomes.
• Author research papers and technical reports that communicate novel findings to the broader scientific and industry community.
• Build and maintain benchmarks and evaluation methodologies to rigorously measure model performance, quality, and progress over time.
• Investigate hard, open-ended problems (e.g., 3D segmentation, articulation, geometry reconstruction) and translate promising results into approaches the engineering team can productionize.
• Collaborate with ML engineers and simulation engineers to hand off validated research and shape the technical roadmap.
• Stay at the frontier of AI/ML literature and continuously bring emerging techniques into our research agenda.

Requirements

• Advanced degree (MS/PhD) in Computer Science, Machine Learning, or a related field, or equivalent research experience.
• Track record of research contributions, ideally including published papers at top venues (CVPR, ICCV, NeurIPS, ICLR, SIGGRAPH, CoRL, etc.).
• Deep expertise in one or more of: computer vision, generative models, 3D deep learning, or robotics/embodied AI.
• Strong experience designing benchmarks, evaluation protocols, and reproducible experiments.
• Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
• Ability to work from first principles on ambiguous, unsolved problems and communicate findings clearly to both technical and non-technical stakeholders.
• Strong scientific writing and presentation skills.