Member of Technical Staff, Microsoft Robotics (Platform)

Microsoft•Redmond, WA

About The Position

Microsoft’s Discovery and Quantum (MDQ) division develops advanced AI, cloud-enabled capabilities, and strategic technologies. Microsoft Robotics, within MDQ, builds technologies that enable people, robots, and AI agents to collaborate. Its robotics platform brings together robotics AI models, teaming solutions, physically grounded agentic AI workflows, trustworthy testing and evaluation, and customer-focused validation to help robotics solutions move from experimentation to reliable, scaled deployment. The Member of Technical Staff contributes to the design, development, and testing of core Microsoft Robotics platform infrastructure, including SDKs, cloud services, edge runtimes, developer tooling, and agent orchestration layers. The role builds well-scoped features with guidance from experienced engineers, explores design options, and develops expertise in robotics software systems while helping bring autonomy capabilities to life. The position also works with autonomy, simulation, and evaluation teams to support robotics and machine-learning workloads.

Requirements

Bachelor’s degree in Computer Science or a related technical discipline, with proven coding experience in languages such as C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.

Nice To Haves

Master’s degree in Computer Science or a related technical field with proven coding experience in languages such as C, C++, C#, Java, JavaScript, or Python; or a bachelor’s degree in Computer Science or a related technical field plus at least two years of technical engineering experience with coding in those languages; or equivalent experience.
Experience contributing to software projects involving developer tools, SDKs, APIs, or distributed systems through coursework, personal projects, internships, research, open-source contributions, or professional work.
Experience coding in one or more of C++, Rust, Go, or Python, with 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 and reviewing, testing, and validating AI-generated code.
Ability to compare and communicate design options, considering latency, reliability, safety, and maintainability, and to incorporate feedback.
Familiarity with cloud services and distributed systems concepts such as microservices, containerized workloads (e.g., Kubernetes), APIs, or CI/CD; Azure exposure is a plus.
Familiarity with API design and integration concepts such as versioning and backward compatibility, and interest in learning how multi-tenant platforms support internal developers and external partners.
Familiarity with robotics middleware (ROS/ROS2), real-time systems, or edge computing, and interest in learning how latency, reliability, and safety requirements affect software deployed to physical systems.
Understanding of agentic AI architectures, including agent orchestration, tool use, multi-agent coordination, and human-in-the-loop workflows, and their application to physical systems.
Familiarity with ML infrastructure such as model serving (ONNX, TensorRT, Triton), training orchestration, experiment tracking, or feature stores, particularly for deploying learned models to edge devices.
Exposure to simulation tools, digital twins, or automated testing, and interest in using physics-based simulation to validate robotics software and catch regressions.

Responsibilities

Implement and test features in platform components, including robotics SDKs, cloud-hosted APIs, edge runtimes, and agent orchestration frameworks for composing autonomy capabilities into deployable mission workflows.
Contribute to platform extensibility and integration, including integrating, versioning, testing, and deploying autonomy capabilities, models, partner hardware, and customer-specific logic across cloud and edge environments.
Develop and test robotics lifecycle data infrastructure, such as instrumentation libraries, data acquisition services, human-in-the-loop workflows, and dataset versioning and curation pipelines.
Apply established security, compatibility, and performance practices to assigned features, including cloud-edge authentication and authorization, API versioning and backward compatibility, and multi-tenant isolation.
Help test and investigate performance against latency requirements for real-time robotic control loops.
Improve the platform developer experience by contributing CLI features, SDK functionality, documentation, sample code, and inner-loop workflow improvements, and incorporating feedback from developers and partners.
Use AI-assisted development tools and agentic coding workflows to improve engineering productivity and software quality.
Contribute to agent-based engineering solutions that automate repetitive tasks, speed investigation and root cause analysis, and strengthen testing, validation, and operational reliability; review and verify AI-generated changes according to team standards.
Collaborate with autonomy, simulation, and evaluation teams to understand requirements and implement and test platform primitives such as compute orchestration, data routing, model serving, and experiment tracking.
Help support performance, reliability, and reproducibility for ML training, sim-to-real transfer, and online evaluation workloads.
Participate in technical design and code reviews, document assigned feature designs, and incorporate feedback from experienced engineers.
Follow team standards for code quality, testing, and operational readiness, and communicate progress, questions, and blockers.
Embody Microsoft’s Culture and Values.