Principal AI Back-End Network Systems Lead
Job Location:
Mountain View, CA - USA
Yearly Salary:
Posted:
Application Deadline:
Vacancies:
Job Summary
Microsoft Silicon Cloud Hardware and Infrastructure Engineering (SCHIE) is the team behind Microsofts expanding Cloud Infrastructure and is responsible for powering Microsofts Intelligent Cloud mission. SCHIE delivers the core infrastructure and foundational technologies that support Microsoft Azure and other online services globally. Our focus is on smart growth high efficiency reliability and a trusted experience for customers and partners worldwide.
The Platform Systems Engineering (PSE) team is seeking a Principal AI Back-End Network Systems Leadto serve as the technical lead and end-to-end product development owner for Back End Network across both scale-up and scale-out. The role will lead the product from requirements and architecture through design integration validation manufacturing readiness deployment and fleet learning - spanning silicon network adapters switches interconnects optics/electrical channels and the fabric as a complete system.
The successful candidate will bring deep expertise in one or more AI/ML scale-up or scale-out networking domains and the product-level thinking to connect decisions across the full system. This lead will work from physical and data-link technologies through network and transport behavior to collectives workloads modeling observability and datacenter deployment creating clarity across architecture execution quality performance reliability power cost and schedule.
#azure #MAIA #AI/ML #Networking #ScaleUp #ScaleOut
Responsibilities
End-to-End Product Ownership & Architecture
- Own the Back End Network product definition and execution plan across scale-up and scale-out from customer/workload needs and product requirements through architecture development qualification deployment and fleet learning.
- Translate AI training and inference requirements into measurable system targets for bandwidth latency scale collective efficiency reliability availability serviceability power thermal behavior cost security and schedule.
- Make and drive cross-system architecture decisions interface contracts feature priorities and risk tradeoffs; maintain clear ownership milestones entry/exit criteria and product readiness metrics.
- Lead NUDD (new unique different and difficult) technology assessments prototypes make/buy/partner decisions and mitigation plans for the highest product risks.
Scale-Up/Scale-Out Systems Silicon Switch & Fabric
- Lead architecture and integration across accelerator and networking silicon NICs/DPUs PHYs/retimers switch ASICs switches cables/backplanes optics and fabric topology.
- Define scalable scale-up and scale-out architectures including topology radix reach link speeds routing path diversity oversubscription failure domains and resiliency.
- Drive silicon board switch firmware network operating system and fabric requirements so that components operate as one high-performance and serviceable product.
- Partner with silicon switch optical cable connector system manufacturing and supplier teams to deliver designs from concept through production and datacenter integration.
Optical/Electrical & Cross-Layer Integration
- Oversee electrical and optical technologies for high-speed links including signal integrity SerDes/PHY link training FEC reach power thermal mechanical manufacturability and interoperability tradeoffs.
- Drive end-to-end behavior across the relevant OSI layers - physical data link network and transport - and the system/runtime interfaces above them.
- Define and validate Ethernet/RDMA or other scale-up/scale-out protocol behavior including flow control congestion control QoS routing packet loss/recovery telemetry and security.
- Ensure hardware firmware drivers network operating systems management software orchestration and datacenter operations are aligned to common specifications and concepts of operation.
Collectives Workloads Modeling & Performance
- Connect network architecture to distributed AI workloads parallelism strategies traffic patterns and collective operations such as all-reduce all-gather reduce-scatter and all-to-all.
- Establish analytical and simulation models for topology bandwidth latency congestion failure behavior collective efficiency workload scaling power and cost.
- Use models emulation prototypes and lab/fleet data to predict bottlenecks guide design choices set performance budgets and validate architectural assumptions.
- Partner with workload collective-communication compiler/runtime and application teams to co-optimize the network and improve job completion time and cluster efficiency.
Validation Reliability Deployment & Operations
- Own the end-to-end validation strategy covering functionality interoperability performance scale stress resiliency reliability security serviceability and upgrade/recovery behavior.
- Lead bring-up and root-cause analysis across silicon electrical/optical links switch fabric protocol system software collective and workload layers using telemetry packet captures counters diagnostics and lab characterization.
- Define production qualification manufacturing test deployment monitoring rollback and fleet-health requirements; use operational learning to drive corrective actions and next-generation improvements.
- Drive product readiness reviews and ensure the solution can be safely and repeatably deployed operated serviced and scaled in hyperscale datacenters.
Technical Leadership & Ecosystem Execution
- Create clarity and technical alignment across architecture silicon hardware optics firmware networking software validation manufacturing datacenter and workload teams.
- Influence internal roadmaps and external partners including silicon switch optical interconnect ODM/OEM and open-source ecosystems; resolve cross-team gaps and ambiguous ownership.
- Communicate product status architectural decisions risks tradeoffs and executive asks clearly while mentoring engineers and raising the quality of end-to-end systems engineering.
Qualifications
- Masters Degree in Electrical Engineering Computer Engineering Mechanical Engineering or related field AND 7 years technical engineering experience
- OR Bachelors Degree in Electrical Engineering Computer Engineering Mechanical Engineering or related field AND 8 years technical engineering experience
- OR equivalent experience
Other Requirements:
- 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.
Preferred Qualifications:
- Bachelors degree in Electrical Engineering Computer Engineering Computer Science or a related technical field and 10 years of relevant experience in networking distributed systems accelerator platforms or cloud infrastructure
- or equivalent experience.
- 6 years of experience designing developing integrating or validating networking for AI/ML HPC accelerator or large-scale cloud systems.
- Deep hands-on expertise in at least one AI/ML networking domain such as scale-up interconnects and silicon/SerDes/PHY electrical or optical connectivity switch systems scale-out Ethernet/RDMA fabrics transport/congestion control collective communication or workload/fabric performance.
- Demonstrated experience leading a complex hardware/software product or subsystem through requirements architecture development integration validation and production deployment.
- Experience architecting or delivering both scale-up and scale-out networks for large AI training or inference systems.
- Experience with high-speed electrical and optical technologies SerDes/PHY FEC signal integrity link training retimers cable/backplane design pluggable or co-packaged optics and 400G/800G or faster links.
- Experience with switch ASICs and systems NICs/DPUs Ethernet RDMA/RoCE routing QoS ECN/PFC/DCQCN or related congestion-control methods SONiC/Linux networking and network operating systems.
- Understanding of collective communication libraries and operations distributed training parallelism AI workload traffic patterns and workload-driven network optimization.
- Experience with network and system modeling simulation emulation performance analysis topology studies traffic generation or collective/workload scaling analysis.
- Experience developing automated validation stress reliability interoperability telemetry diagnostics observability and fleet-health frameworks.
- Track record of system bring-up and cross-layer debug from physical links through protocol runtime collectives and application behavior.
- Experience driving manufacturing readiness supplier/partner execution datacenter deployment serviceability and fleet operations for hardware-intensive products.
- Strong product judgement technical leadership collaboration written communication and executive presentation skills.
Hardware Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142800 - $274800 per year. There is a different range applicable to specific work locations within the San Francisco Bay area and New York City metropolitan area and the base pay range for this role in those locations is USD $188000 - $304200 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
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
