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Salary: USD 165,600 - 296,400 / annual
Microsoft's Discovery and Quantum (MDQ) division is seeking a Member of Technical Staff at the Principal level to lead the development of physics-ready 3D asset generation pipelines and integration of reality capture technologies into Microsoft's robotics simulation infrastructure. This role bridges the physical and simulated worlds by creating high-fidelity digital representations of real-world environments, objects, and robots.
You will design and build automated pipelines for converting reality capture data (photogrammetry, LiDAR point clouds, depth camera scans, 360-degree imagery) into physics-ready 3D simulation assets with accurate geometry, collision meshes, material properties, and articulation definitions. Key responsibilities include developing and maintaining toolchains for physics-ready 3D asset generation, including mesh optimization, UV unwrapping, PBR material assignment, collision hull generation, mass/inertia parameter estimation, and annotation of semantic and functional properties.
You will integrate reality capture hardware and software workflows (e.g., NeRF, Gaussian splatting, structured light scanning, photogrammetry reconstruction) with the simulation platform's asset ingestion pipeline. You'll build 3D reconstruction workflows that enable rapid creation of simulation environments from real-world facility scans, supporting robotics deployment planning, testing, and validation. You will create and maintain asset toolchains supporting industry-standard formats (USD/OpenUSD, glTF, FBX, OBJ) with appropriate physics and simulation metadata for import into robotics simulation engines.
Additional responsibilities include developing synthetic data generation pipelines that leverage high-fidelity 3D assets to produce training data for perception, manipulation, and navigation models, including domain-randomized variations of materials, lighting, object placement, and camera viewpoints. You will collaborate with robotics engineers, ML researchers, and perception scientists to define asset fidelity requirements, validate simulation-to-reality visual and physical accuracy, and iterate on asset quality based on downstream model performance. You will implement quality assurance and validation workflows for 3D assets, including automated checks for mesh integrity, physics parameter consistency, rendering fidelity, and simulation stability. Code review and technical design oversight are part of the role to ensure adherence to team standards. You will remain current in 3D reconstruction, neural rendering, and asset generation research, proactively evaluating new techniques for integration into the platform.
Requirements:
Required: Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Must be able to meet Microsoft, customer, and/or government security screening requirements, including Microsoft Cloud Background Check (required upon hire and every two years thereafter).
Preferred: Master's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in C, C++, C#, Java, JavaScript, or Python; OR Bachelor's Degree in Computer Science or related technical field AND 15+ years technical engineering experience. Experience with 3D reconstruction pipelines, photogrammetry, LiDAR processing, or neural scene representation methods (NeRF, 3D Gaussian splatting). Proficiency with 3D content creation and processing tools (Blender, Fusion, Maya, Houdini, MeshLab, Open3D, or equivalent). Experience with USD/OpenUSD, OBJ, STL, or equivalent 3D interchange formats and their integration with simulation or rendering engines. Background in physically based rendering (PBR), material authoring, or real-time graphics pipeline development. Experience building synthetic data generation pipelines for training computer vision or perception models. Familiarity with robotics simulation platforms (Isaac Sim, Gazebo, MuJoCo, or equivalent) and their asset requirements. Understanding of physics parameter estimation, collision geometry optimization, and articulated object modeling for simulation fidelity.
