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Microsoft Silicon, Cloud Hardware, and Infrastructure Engineering (SCHIE) is the team behind Microsoft's expanding Cloud Infrastructure and responsible for powering Microsoft's 'Intelligent Cloud' mission. SCHIE delivers the core infrastructure and foundational technologies for Microsoft's over 200 online businesses including Bing, MSN, Office 365, Xbox Live, Teams, OneDrive, and the Microsoft Azure platform globally with our server and data center infrastructure, security and compliance, operations, globalization, and manageability solutions. Our focus is on smart growth, high efficiency, and delivering a trusted experience to customers and partners worldwide and we are looking for passionate engineers to help achieve that mission.
As a Senior Network Systems Engineer team member, you will work directly with engineers across cross‑functional teams and deliver Network hardware designs from concept to data center deployment. Responsibilities will include interacting directly with Microsoft Azure's services teams, cross‑discipline design teams focusing on the functional interfaces and developing scale up and scale out AI/ML infrastructure rack designs. This is an opportunity to leverage and grow your existing networking hardware design/validation experience and provide innovative E2E hardware solutions to Microsoft Cloud to support AI/ML development.
Responsibilities
Collaborate with architecture, silicon engineering, firmware, hardware design, hardware validation, OS (operating systems), manufacturing, and customer teams to build state‑of‑the‑art accelerator hardware solutions.
Participate in architectural discussions and evaluate networking performance required to meet the demands of AI/ML workloads.
Analyze new interfaces and subsystems to develop integration plans, analyze power efficiency, debug integration issues, and provide recommendations.
Define system behavior and concept of operations for the platform to ensure compatibility with Microsoft Azure datacenter software, serviceability, telemetry, and customer expectations.
Perform NUDD (new, unique, different and difficult) technology and feature analysis and provide risk assessment and mitigations.
Drive technical requirements and ensure the solution is flexible and scalable across the full (HW/FW/SW) stack.
Enable platform and solution level discussions, influencing architecture of the product, and delivering to product goals across quality, reliability, and performance.
Collaborate with internal, external, and open‑source partners to onboard innovative technologies in a seamless manner.
Qualifications Required Qualifications
Master’s Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 3+ years technical engineering experience.
Bachelor’s Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 5+ years technical engineering experience.
Equivalent experience.
8+ years of relevant experience in system (compute, networking, and/or accelerator) level design and/or implementation across the hardware development lifecycle.
5+ years of hands‑on experience in developing AI/ML scale up and scale out networking for accelerator‑based hardware systems, as well as developing MAC/PCS and SERDES for high‑speed interfaces and high‑density connectivity equipment.
5+ years of experience working across multiple disciplines (hardware, firmware, software, and/or data center infrastructure) to identify risks, drive discussions, detail system tradeoffs, and assess impact.
Other Requirements Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.
Preferred Qualifications
8+ years of experience developing GPU, FPGA based accelerator platforms for AI/ML use cases.
Great to have proven track record of bringing up, integrating, and deploying new hardware technology.
Knowledge of high‑volume silicon (SoCs, GPUs, or FPGAs), compute, storage, and/or networking design, manufacturing, and deployment.
Understanding on Networking hardware – QSFP‑dd cables, DACs, AECs, cable backplanes, NICs, PHY, switches.
Ability to define validation test cases to qualify end‑to‑end network across functionality, performance and scale testing.
Ability to troubleshoot network issues at multiple layers – physical layer, data link, network layer, protocol layer.
Great to have: Understanding on AI Network, Network Collectives, Traffic profiles in AI networks, Ultra Ethernet.
Knowledge about datacenters & operations at scale.
Experience managing hardware programs through the entire product lifecycle.
Strong verbal and written communication and presentation skills.
Hardware Engineering IC4 – The typical base pay range for this role across the U.S. is USD $119,800 – $234,700 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here.
Microsoft will accept applications for the role until October 23rd, 2025.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.
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As a Senior Network Systems Engineer team member, you will work directly with engineers across cross‑functional teams and deliver Network hardware designs from concept to data center deployment. Responsibilities will include interacting directly with Microsoft Azure's services teams, cross‑discipline design teams focusing on the functional interfaces and developing scale up and scale out AI/ML infrastructure rack designs. This is an opportunity to leverage and grow your existing networking hardware design/validation experience and provide innovative E2E hardware solutions to Microsoft Cloud to support AI/ML development.
Responsibilities
Collaborate with architecture, silicon engineering, firmware, hardware design, hardware validation, OS (operating systems), manufacturing, and customer teams to build state‑of‑the‑art accelerator hardware solutions.
Participate in architectural discussions and evaluate networking performance required to meet the demands of AI/ML workloads.
Analyze new interfaces and subsystems to develop integration plans, analyze power efficiency, debug integration issues, and provide recommendations.
Define system behavior and concept of operations for the platform to ensure compatibility with Microsoft Azure datacenter software, serviceability, telemetry, and customer expectations.
Perform NUDD (new, unique, different and difficult) technology and feature analysis and provide risk assessment and mitigations.
Drive technical requirements and ensure the solution is flexible and scalable across the full (HW/FW/SW) stack.
Enable platform and solution level discussions, influencing architecture of the product, and delivering to product goals across quality, reliability, and performance.
Collaborate with internal, external, and open‑source partners to onboard innovative technologies in a seamless manner.
Qualifications Required Qualifications
Master’s Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 3+ years technical engineering experience.
Bachelor’s Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 5+ years technical engineering experience.
Equivalent experience.
8+ years of relevant experience in system (compute, networking, and/or accelerator) level design and/or implementation across the hardware development lifecycle.
5+ years of hands‑on experience in developing AI/ML scale up and scale out networking for accelerator‑based hardware systems, as well as developing MAC/PCS and SERDES for high‑speed interfaces and high‑density connectivity equipment.
5+ years of experience working across multiple disciplines (hardware, firmware, software, and/or data center infrastructure) to identify risks, drive discussions, detail system tradeoffs, and assess impact.
Other Requirements Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.
Preferred Qualifications
8+ years of experience developing GPU, FPGA based accelerator platforms for AI/ML use cases.
Great to have proven track record of bringing up, integrating, and deploying new hardware technology.
Knowledge of high‑volume silicon (SoCs, GPUs, or FPGAs), compute, storage, and/or networking design, manufacturing, and deployment.
Understanding on Networking hardware – QSFP‑dd cables, DACs, AECs, cable backplanes, NICs, PHY, switches.
Ability to define validation test cases to qualify end‑to‑end network across functionality, performance and scale testing.
Ability to troubleshoot network issues at multiple layers – physical layer, data link, network layer, protocol layer.
Great to have: Understanding on AI Network, Network Collectives, Traffic profiles in AI networks, Ultra Ethernet.
Knowledge about datacenters & operations at scale.
Experience managing hardware programs through the entire product lifecycle.
Strong verbal and written communication and presentation skills.
Hardware Engineering IC4 – The typical base pay range for this role across the U.S. is USD $119,800 – $234,700 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here.
Microsoft will accept applications for the role until October 23rd, 2025.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.
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