• Design, develop, and evaluate physical world models that capture 3D spatial structure, object geometry and pose, physics dynamics, material properties, and semantic scene understanding for robotic applications.
• Build and train world models (e.g., video prediction models, neural physics simulators, 3D generative models, scene graph representations) that predict future states of physical environments conditioned on robot actions, enabling model-based planning and policy learning.
• Develop spatial AI capabilities including 3D scene reconstruction, object detection and pose estimation, spatial relationship reasoning, occupancy prediction, and dense 3D feature representations for robot perception and planning.
• Implement and maintain evaluation frameworks for world models and spatial AI systems, including prediction accuracy metrics, planning performance benchmarks, and generalization testing across environments and object categories.
• Collaborate with robotics researchers, learning engineers, and simulation engineers to integrate world models into robot planning and control pipelines, enabling model-predictive control, imagination-based planning, and data-augmented training.
• Build data pipelines for training world models, including multi-sensor data fusion (RGB, depth, LiDAR, proprioception), scene annotation, and dataset curation for diverse physical environments and interaction scenarios.
• Write efficient, readable, extensible code in Python (including PyTorch, JAX, or TensorFlow) for model development, training, and evaluation, leveraging GPU computing infrastructure for large-scale experiments.
• Contribute to the formulation of the team’s world modeling research and development roadmap, identifying high-impact technical directions and collaborating with leadership to prioritize investments.
• Present research findings and model evaluation results clearly and efficiently to internal stakeholders and external partners, contributing to technical publications, blog posts, and conference presentations.
• Stay current with state-of-the-art research in world models, spatial AI, 3D vision, neural physics simulation, and foundation models for physical understanding, actively contributing to the body of thought leadership in these areas.

Required Qualifications:

• Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience
• OR equivalent experience.

Preferred Qualifications:

• Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR equivalent experience.
• Strong background in robotics perception, navigation, and proprioceptive sensor stacks and systems integration, including algorithm and model development and implementation in real-world applications.
• Experience with world models, video prediction models, neural physics simulators, or generative 3D models for physical environment understanding and prediction.
• Strong background in 3D computer vision, including depth estimation, 3D reconstruction, NeRF/Gaussian splatting, point cloud processing, or spatial reasoning.
• Proficiency in PyTorch, JAX, or TensorFlow with experience training large-scale models on GPU clusters (Azure Machine Learning, Kubernetes, or equivalent).
• Experience with robotics perception systems, including multi-sensor fusion (RGB-D, LiDAR, proprioception), object pose estimation, or scene graph construction.
• Familiarity with model-based reinforcement learning, model-predictive control, or imagination-based planning approaches that leverage learned world models.
• Published research or demonstrated contributions to world models, spatial AI, 3D vision, neural simulation, or physical AI in top-tier venues (NeurIPS, ICML, ICLR, CoRL, RSS, CVPR, ECCV, or equivalent).
• Experience with the Microsoft Azure AI toolset (Azure Machine Learning, Azure Databricks, Azure Cognitive Services) or equivalent cloud ML platforms.

Data Science IC3 - The typical base pay range for this role across the U.S. is USD $102,100.00 - $202,200.00 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $133,800.00 - $219,200.00 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.