Senior Network HW System Engineer
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Job Summary
Microsoft Silicon Cloud Hardware and Infrastructure Engineering (SCHIE) is the team behind Microsofts expanding Cloud Infrastructure and responsible for powering Microsofts Intelligent Cloud mission. SCHIE delivers the core infrastructure and foundational technologies for Microsofts 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 partnersworldwideand we are looking for passionateengineers to help achieve that mission.
Microsofts Hardware Systems organization is developing AI-native silicon and system-level solutions to power the next generation of frontier AI models. The MAIA platform combines custom accelerators advanced networking technologies large-scale distributed infrastructure and cloud-scale software to deliver industry-leading AI training and inference capabilities.
The Platform Systems Engineering (PSE) team isseekingaAI NetworkHWSystems Engineerto drive the architecture bring-up validation optimization and deployment of networking infrastructure for next-generation MAIA AI systems. This role sits at the intersection of networking hardware systems architecture AI infrastructure and hyperscale deployment.
You will work across the entire networking stack from high-speed SerDes interfaces optics cables NICs PHYs and switch silicon to AI communication frameworks and distributed training workloads. You will collaborate with architects silicon engineers firmware developers hardware designers validation teams OS developers manufacturing partners and Azure service teams to deliver scalable reliable and high-performance AI networking solutions.
This is a unique opportunity to influence the future of AI infrastructure while enabling Microsofts next generation of frontier-scale AI systems.
#azure#MAIA#AI/ML#Networking Hardware
Responsibilities
AI Networking Architecture & Platform Development
Define and drive networking architectures for MAIA AI training and inference platforms spanning scale-up and scale-out deployments. Partner across architecture silicon firmware software and Azure infrastructure teams to deliver networking solutions from concept through datacenter deployment while influencing future networking roadmaps.
Network Hardware Integration & System Bring-Up
Lead the integration bring-up and deployment of network hardware technologies including switches NICs PHYs high-speed SerDes interfaces optics cables and backplane solutions. Collaborate with internal teams ODMs and technology partners to ensure successful qualification andproductionreadiness.
AI Fabric Validation Performance & Reliability
Define and execute validation strategies for AI networking infrastructure includingfunctional performance scale interoperability reliability and stress testing. Develop automated qualification frameworks and methodologies to ensure robust operation in rack-scale and cluster-scale AI environments.
Performance Optimization & Networking Efficiency
Analyze andoptimizeAI fabric performance across distributed training and inference workloads. Evaluate latency bandwidthutilization congestion behavior and collective communication efficiency translating workload requirements into scalable networking solutions and architecture recommendations.
High-Speed Interconnect & Emerging Technologies
Drive qualification and deployment of next-generation networking technologies including high-speed copper and optical interconnects PAM4-based SerDes advanced optics and future networking innovations such as LPO LRO CPO and silicon photonics. Evaluate technology tradeoffs across performance power reliability and scalability.
Debug Telemetry & Automation
Lead root-cause analysis of networking and AI fabric issues spanning physicallayer network protocols and distributed AI communication layers. Develop telemetry diagnostics automation and fleet monitoring solutions that improve network reliability accelerate issue resolution and enhance engineering productivity.
Key Responsibilities
Drive end-to-end architecture integration validation and deployment of networking infrastructure for MAIA AI systems across scale-up and scale-out environments.
Partner with silicon firmware software hardware and Azure infrastructure teams to define networking requirements and deliver scalable reliable and high-performance AI fabrics.
Lead bring-up qualification and optimization of network subsystems including switches NICs PHYs optics cables and high-speed SerDes technologies.
Develop validation and performance methodologies for AI networking infrastructure ensuring readiness across functionality scale reliability and stress conditions.
Drive root-cause analysis telemetry and automation solutions to improve network resiliency operational efficiency and fleet health.
Evaluate and influence next-generation networking technologies and architecturesrequiredto support future AI workloads and hyperscale deployments.
Qualifications
Preferred Qualifications
AI Infrastructure Experience
Experience developing GPU FPGA TPU AI accelerator or HPC-based systems.
Familiarity with AI workload communication patterns and collective operations.
Understanding oflarge-scale distributed AI training environments.
Optical & Interconnect Expertise
Deep knowledge of:
Optical transceivers (DR4 DR8 FR4)
DSP architectures
TIAs and drivers
Optical link budgets
OMA TDECQ receiver sensitivity analysis
Silicon photonics technologies
Co-packaged optics architectures
Industry Standards
Experience with:
IEEE Ethernet standards
OIF specifications
CMIS management frameworks
Ultra Ethernet Consortium technologies
Future 224G and 448G ecosystems
Datacenter & Manufacturing
Experience with hyperscale datacenter deployments.
Knowledge of ODM CM and supplier ecosystems.
Experience managing products through EVT DVT PVT and production ramps.
Software & Automation
Experience with Linux environments and automation frameworks.
Background developing telemetry diagnostics validation andqualificationtooling.
Familiarity with scripting and data analysis environments.
This position will be open for a minimum of 5 days with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age ancestry citizenship color family or medical care leave gender identity or expression genetic information immigration status marital status medical condition national origin physical or mental disability political affiliation protected veteran or military status race ethnicity religion sex (including pregnancy) sexual orientation or any other characteristic protected by applicable local laws regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process read more about requesting accommodations.
Required Experience:
IC
