Applied Researcher – Network Expert

Designworks Talent LLC

. Hold the company's view of where AI networking is going .

Posted 9/20/2026full-timeBellevue • Washington • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates deep expertise in networking at scale, particularly with GPU clusters and high-performance computing environments. Capable of evaluating technologies, debugging performance issues, and influencing engineering decisions across teams.

Highest-signal resume keywords

Networking At ScaleGPU Cluster ExperienceInfiniBand ProficiencyNCCL/RCCL DebuggingMulti-Tenant Network Isolation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

High-Performance ComputingInter-GPU NetworkingOptics UnderstandingTelemetry AnalysisCluster Performance DebuggingAI Infrastructure KnowledgeScale-Up/Scale-Out FabricCost-Per-Port AnalysisData Center CollaborationTechnical Diligence

Soft Skills

Analytical SkillsTechnical CommunicationCollaborationInfluencing Without AuthorityOwnership

Tools & Technologies

NVIDIA GPU InfrastructureAMD GPU InfrastructureInfiniBandRoCEv2Spectrum-XUltra EthernetNVLinkNVSwitch

Industry Keywords

AI NetworkingNetworking FabricsStandards BodiesHPC FabricsVendor RoadmapsPerformance AnalysisData Center OperationsMulti-Tenant IsolationResearch ExperienceU.S. Export Control

About the role

Key responsibilities & impact

Hold the company's view of where AI networking is going
Track vendor and hyperscaler roadmaps, research, standards work, and the startup and venture landscape across networking fabrics, topology, optics, collectives, software, operations, telemetry, and tenant-facing capability
Formulate and validate product and engineering theses using measured cluster performance, isolation requirements, and cost per port
Own the company's fabric position, including scale-up/scale-out boundaries, transport choices, telemetry, and observability
Help finance formulate cost-per-port, optics, cabling, reach, power, failure-rate, and substantiated performance analyses
Own tenant-facing network capability for GPU-as-a-service, including multi-tenant isolation, storage traffic, and contractual commitments
Support sales and delivery in demanding customer conversations about cluster performance
Feed product and go-to-market teams with offerings, performance, and pricing information
Provide technical diligence on network vendors, partners, and prospective tuck-in targets
Collaborate with the Data Center Expert where the fabric meets the physical plant

Requirements

What you’ll need

Deep professional experience in networking at scale
Hands-on experience with high-performance GPU or HPC fabrics at current generations
Demonstrated experience debugging real collective communication performance problems in production
Fluency with switch, NIC, and optics vendors, standards bodies and consortia, and startups attacking the fabric layer
Applied research experience investigating open questions from primary sources and producing defensible positions under uncertainty
A PhD in a relevant technical field is valued, but sustained industry research, standards-body work, or internal technical assessments that changed decisions are equally valid
Deep professional experience in computer networking and large-scale infrastructure
Significant experience with GPU clusters, AI infrastructure, or high-performance computing environments
Strong understanding of inter-GPU networking
Hands-on experience with InfiniBand at current generations (NDR/XDR), high-performance Ethernet fabrics (RoCEv2, Spectrum-X, or Ultra Ethernet), or comparable HPC interconnects
Practical understanding of NVLink/NVSwitch scale-up domains and interaction with scale-out fabric
Experience debugging NCCL/RCCL collective communication performance problems, congestion, stragglers, and topology mismatch
Understanding of multi-tenant network isolation and related security and performance tradeoffs
Understanding of large-scale AI cluster configurations and networking requirements for thousands of GPUs
Ability to evaluate competing technologies and understand networking industry direction
Familiarity with NVIDIA and AMD GPU infrastructure ecosystems
Strong analytical and technical communication skills
Ability to operate as a horizontal technical expert and influence engineering decisions without necessarily owning implementation
Ability to read technical papers and translate research concepts into practical engineering implications
Ability to operate across engineering, research, and infrastructure organizations
Track record collaborating with researchers and engineers across groups and levels
Comfortable operating as an individual contributor with high ownership in a lean, early-stage team
U.S. work authorization required
Visa sponsorship is not currently available
Eligibility may be subject to U.S. export control screening and, where applicable, licensing
Willingness and ability to travel internationally to data centers and co-locations, up to 25%

Benefits

Comp & perks

Directly influence the technology direction of an organization building AI infrastructure at scale
Help establish technical strategy, architecture, processes, and culture within a growing organization
High ownership with substantial autonomy and direct access to senior technical leadership
Cross-disciplinary exposure across AI models, inference, accelerators, software systems, networking, infrastructure, and economics
Work on cutting-edge technical problems involving multi-accelerator inference, intelligent routing, performance optimization, token economics, and compiler, kernel, and runtime technologies
Research with practical impact on engineering, product, commercial strategy, and investment
Work with a small group of highly experienced technical contributors rather than within a large management hierarchy