Member of Technical Staff, Microsoft Robotics (Platform)

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 to contribute to the design, development, and testing of core infrastructure components of the Microsoft Robotics platform, including the Software Development Kits (SDKs), cloud services, edge runtimes, developer tooling, and agent orchestration layers that enable people, AI agents, and robots to operate together across end-to-end mission workflows. In this role, you will build well-scoped features with guidance from experienced engineers, explore design options, and develop your skills in robotics software systems while helping bring autonomy capabilities to life. 

• Implement and test features within core platform components with guidance, including robotics SDKs, cloud-hosted Application Programming Interfaces (APIs), edge runtimes, and agent orchestration frameworks that enable developers and partners to compose interoperable autonomy capabilities (perception, planning, control, multi-agent coordination) into deployable mission workflows. 

• Contribute to platform extensibility and integration features using established patterns, helping integrate, version, test, and deploy first-party autonomy capabilities, first- and third-party models, partner hardware systems, and customer-specific logic across cloud and edge environments. 

• Develop and test components of data infrastructure for the robotics lifecycle, such as instrumentation libraries, data acquisition services, human-in-the-loop workflows, and dataset versioning and curation pipelines, applying established data quality practices to real-world and synthetic/simulated data with guidance from the team. 

• Apply established security, compatibility, and performance practices to assigned features with guidance, including authentication and authorization across cloud-edge boundaries, API versioning and backward compatibility, and multi-tenant isolation. Help test and investigate performance against the latency requirements of real-time robotic control loops. 

• Help improve the developer experience for the Microsoft Robotics platform by contributing Command Line Interface (CLI) features, SDK functionality, documentation, sample code, and inner-loop workflow improvements, following team patterns and incorporating feedback from internal developers and external partners. 

• Use AI-assisted development tools, such as GitHub Copilot, and agentic coding workflows to improve engineering productivity and software quality. Contribute to agent-based engineering solutions that automate repetitive tasks, accelerate investigation and root cause analysis, and strengthen testing, validation, and operational reliability, applying team standards for code review and verification of AI-generated changes. 

• Collaborate with autonomy, simulation, and evaluation teams to understand requirements and implement and test assigned features in platform primitives (compute orchestration, data routing, model serving, experiment tracking), helping support the performance, reliability, and reproducibility needs of Machine Learning (ML) training, sim-to-real transfer, and online evaluation workloads. 

• Participate in technical design and code reviews, contribute to design documentation for assigned features, and incorporate feedback from experienced engineers. Apply team standards for code quality, testing, and operational readiness, and communicate progress, questions, and blockers. 

Other:

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