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Member of Technical Staff, Microsoft Robotics (Perception)
MicrosoftUnited Statesfull_timeVerifiedPosted 29 May 2026
💰 $261,000/yr($119,800/yr – $261,000/yr)
About the role
Overview
#MicrosoftRobotics #MDQ
Responsibilities
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 (Perception) at the Senior level, to lead the development of perception, localization, mapping, and navigation capabilities that enable robots to understand and move through complex physical environments. This engineer will design and integrate production-quality autonomy systems that combine multi-sensor perception, SLAM, state estimation, semantic mapping, spatial reasoning, and navigation planning into reliable robot behavior. The role bridges advanced perception algorithms, physical world modeling, navigation stacks, simulation, and real-world deployment, with an emphasis on turning research-grade capabilities into robust systems that operate under latency, reliability, safety, and field-readiness constraints. This engineer will help define how Microsoft’s robotics platform perceives, represents, reasons about, and navigates the physical world across heterogeneous robots, environments, and customer scenarios.
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.
#MicrosoftRobotics #MDQ
Responsibilities
- Lead the design, development, and integration of perception and navigation systems for robotic platforms, including SLAM, localization, mapping, sensor fusion, obstacle detection, semantic scene understanding, and motion planning interfaces.
- Develop robust state estimation and localization pipelines using data from cameras, depth sensors, LiDAR, IMUs, wheel odometry, proprioception, GPS, force/torque sensors, or other robot sensor modalities.
- Build spatial representations for navigation and planning, including occupancy maps, semantic maps, costmaps, 3D scene representations, traversability maps, object-level representations, and dynamic environment models.
- Integrate perception outputs with planning, control, simulation, and fleet operations systems to support safe and reliable robot autonomy in real-world environments.
- Architect perception-navigation pipelines that meet practical constraints for latency, bandwidth, compute efficiency, reliability, calibration drift, sensor degradation, and environmental variability.
- Develop evaluation frameworks, benchmarks, and telemetry-driven analysis methods to measure perception, localization, mapping, and navigation performance across simulation, lab, and field deployments.
- Partner with learning engineers, spatial AI engineers, simulation engineers, and platform engineers to connect classical robotics pipelines with modern AI models, including learned perception, physical world models, and data-driven navigation approaches.
- Analyze field logs, sensor data, planner behavior, and failure cases to identify root causes, improve system robustness, and drive cross-stack improvements across perception, planning, controls, and hardware integration.
- Lead technical design reviews, establish engineering patterns, and mentor other engineers on production-quality robotics autonomy development, testing, debugging, and deployment practices.
- Stay current with stat
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