Microsoft
Member of Technical Staff, Microsoft Robotics (Platform)
Redmond, WA, US · Staff+
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About the role
- 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
Nice to have
- Help test and investigate performance against the latency requirements of real-time robotic control loops.
- Use AI-assisted development tools, such as GitHub Copilot, and agentic coding workflows to improve engineering productivity and software quality.
- Apply team standards for code quality, testing, and operational readiness, and communicate progress, questions, and blockers.
- Experience coding in one or more of C++, Rust, Go, or Python, with an interest in systems-level components, tooling, data pipelines, or ML integration and an emphasis on clear, maintainable, testable code.
- Experience using AI-assisted development tools, such as GitHub Copilot, including exposure to agentic coding workflows, with an emphasis on reviewing, testing, and validating AI-generated code.
- Familiarity with cloud services and distributed systems concepts, such as microservices, containerized workloads (e.g., Kubernetes), APIs, or CI/CD
- exposure to Azure is a plus.
- Understanding of agentic AI architectures, including agent orchestration, tool use, multi-agent coordination, and human-in-the-loop workflows, and how they apply to physical systems.
This listing is sourced directly from Microsoft's careers page and normalized into a canonical job model.