Hardware Engineer - MDQ OCTO

Microsoft•Redmond, WA

About The Position

Microsoft's Discovery and Quantum (MDQ) division develops and delivers advanced Artificial Intelligence (AI), cloud capabilities, and strategic technologies to help solve the world’s major challenges. From accelerated scientific discovery through advanced AI, to breakthroughs in quantum computing, to unique AI and edge platforms for bio-intelligence and biosecurity, and to advanced robotics and AI capabilities to accelerate positive impact in the physical world, joining MDQ means building the future, partnering with high-paced innovators, and working in an exhilarating, impact-focused environment. Within MDQ’s Office of the CTO (OCTO), our mission spans advancing how intelligent systems perceive, reason, and act in the physical and digital worlds. We are transforming robots from tools into teammates, empowered by next-generation AI models and grounded in trustworthy autonomy principles. Our goal is to create seamless collaboration among humans, robots, and AI agents to accelerate relevance to real-world applications such as scientific discovery and commercial scenarios. Through this convergence of AI and robotics, we are positioning Microsoft at the forefront of a new era where agentic AI and embodied systems work alongside humans to achieve breakthroughs in productivity, physical tasks, and scientific exploration. As a Hardware Engineer – MDQ OCTO, you will build and operate the physical systems and lab infrastructure that enable cloud‑to‑edge robotics—from early lab bring‑up to production‑ready systems deployed in the real world.

Requirements

Bachelor's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field OR equivalent experience.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

Nice To Haves

Master's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field OR Bachelor's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 2+ years technical engineering experience OR equivalent experience.
Experience with robotic systems, including compute modules, cameras, inertial measurement units (IMUs), light detection and ranging (LiDAR) sensors, networking, and power systems.
Experience with Linux-based systems, embedded constraints, and on-device debugging.
Experience developing or executing software and hardware-in-the-loop (SIL/HIL) or system-level test strategies.
Experience working with manufacturers, suppliers, and partners.

Responsibilities

Robotics Lab Infrastructure & Operations
Own safe, reliable, and scalable robotics lab environments, including safety practices, access controls, and operational procedures for human–robot interaction.
Manage the full lifecycle of lab hardware and shared test assets, including inventory, maintenance, upgrades, and decommissioning.
Enable efficient system bring‑up and experimentation through standardized lab configurations, golden images, checklists, instrumentation, and calibration workflows.
Evolve lab operations to support repeatable, scalable development as programs and team footprint grow.
Robotics Systems & Platform Engineering
Contribute to the design and integration of robotics hardware platforms across compute, sensing, power, networking, mechanical, and software domains.
Apply device specifications and interface requirements to support reliable system design, validation, and integration.
Participate in system‑level architecture discussions and design reviews, evaluating tradeoffs across performance, safety, reliability, cost, and scalability.
Define and implement clear interfaces to enable parallel, cross‑team development.
Systems Integration & Field Deployment
Integrate hardware and software into end‑to‑end robotic systems supporting lab, simulation, and real‑world deployments.
Diagnose and resolve cross‑domain integration and reliability issues (compute, sensing, power, electromagnetic and radio-frequency interference (EMI/RFI), thermal, timing, networking, and safety).
Support simulation, software and hardware-in-the-loop (SIL/HIL), instrumentation, and data capture workflows to de‑risk field deployments and improve system robustness.
Develop repeatable bring‑up, commissioning, recovery, and field‑support procedures; document findings and drive post‑test improvements.
Supplier & Partner Collaboration
Support technical evaluation, procurement analysis, commissioning, and acceptance of partner‑delivered systems.
Collaborate with suppliers and integrators to resolve integration issues, track corrective actions, and improve long‑term quality and reliability.
Contribute integration guides, acceptance criteria, and internal knowledge transfer for partner components and systems.
Documentation, Automation & Knowledge Sharing
Create clear technical documentation and operational guidance to support onboarding and cross‑team collaboration.
Automate lab, testing, and data‑collection workflows where appropriate to improve consistency and efficiency.
Share best practices and lessons learned across teams as a technical ambassador.