Member of Technical Staff, Microsoft Robotics (Spatial AI)

Microsoft•Redmond, WA

6d•$102,100 - $219,200

About The Position

Microsoft’s Discovery and Quantum (MDQ) division develops and delivers advanced artificial intelligence (AI), cloud-enabled capabilities, and strategic technologies to help solve the world’s major challenges. From accelerating scientific discovery with advanced AI tools, to pioneering breakthroughs in quantum computing, to advancing robotics and AI capabilities that drive real-world impact, joining MDQ means building the future, partnering with fast-moving innovators, and operating in a high-impact, mission-driven environment. At Microsoft Robotics within MDQ, we build and deploy technologies that enable people, robots, and AI agents to collaborate and achieve more. We are building Microsoft’s platform for physical intelligence—an integrated robotics software and AI platform that brings together humans, robots, and agents through robotics AI models, innovative teaming solutions and experiences, physically grounded agentic AI workflows, trustworthy test and evaluation, and real-world customer-focused validation. Built on Microsoft’s core platforms and delivered through and with a global ecosystem of partners and customers, this platform accelerates AI for the physical world and helps robotics solutions move from experimentation to reliable, scaled deployment. We are hiring a Member of Technical Staff, Microsoft Robotics (Spatial AI) at the data & applied science II level, to design, develop, and test physical world models that enable robots to understand, predict, and reason about the 3D physical environments in which they operate. This role focuses on building models that capture spatial structure, object relationships, physics dynamics, and scene semantics, providing robots with the physical intuition needed for manipulation, navigation, and interaction planning. The engineer will work at the frontier of world modeling, spatial AI, and foundation models for robotics, contributing to models that predict how the physical world changes in response to robot actions and environmental dynamics. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Requirements

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.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

Nice To Haves

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.

Responsibilities

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.