Member of Technical Staff, Microsoft Robotics; Software Systems

Position: Member of Technical Staff, Microsoft Robotics (Software Systems)
Overview

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 (Software Systems) at the Senior level, to own the reliability, observability, and operational health of our production robotics platform - spanning Azure-hosted cloud services, on-robot edge runtimes, and the data and telemetry systems that connect them. This is an individual contributor role with deep hands-on ownership: you will be the engineer who builds and operates the production infrastructure that keeps physical AI systems running safely and reliably s role sits at the intersection of site reliability engineering (SRE) and robotics systems engineering;

you will ensure that the software powering real-world robots in partner and customer environments is safe, performant, monitorable, and recoverable.

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.

#Microsoft Robotics #MDQ

Responsibilities

* Design, build, and operate the observability and monitoring infrastructure for the Microsoft Robotics platform, including telemetry pipelines, distributed tracing, alerting, dashboards, and health models that span cloud services on Azure and edge/on-robot components running in partner environments.

* Instantiate the core incident response and reliability capabilities for production robotics workloads, to include defining Service Level Indicators (SLIs)/Service Level Objectives (SLOs), building automated detection and remediation, conducting post-incident reviews, and driving systemic improvements that prevent recurrence across the fleet.

* Engineer production-grade deployment and release pipelines for robotics software, including safe rollout strategies for edge/on-robot updates, canary deployments, rollback automation, and stage-gated release processes that enforce safety and quality checks before software reaches physical systems.

* Build and maintain the secure-by-design infrastructure for cloud-to-edge communication, including certificate management, secure boot chains, encrypted telemetry channels, and access controls for remotely managed robotic systems.

* Partner with platform, autonomy, and simulation engineers to instrument new capabilities with production-quality logging, metrics, and tracing from day one, embedding operational readiness into the development lifecycle rather than retrofitting it.

* Develop capacity planning models and performance baselines for robotics workloads, identifying scaling bottlenecks in data ingestion, model inference, simulation execution, and real-time control loops before they impact partner deployments.

* Contribute to…