Applied Researcher – AI Expert

Designworks Talent LLC

. Hold the company's view of the future direction of data center infrastructure .

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

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI model technologies, including hands-on experience with inference and accelerator ecosystems. Capable of influencing cost models and collaborating across engineering, product, and finance teams to drive data center infrastructure strategies.

Highest-signal resume keywords

Hands-On Experience With Modern AI ModelsDepth In Inference TechnologiesWorking Fluency In Accelerator EcosystemsTechnical Diligence On Infrastructure PartnersExperience With Major Model Types

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Inference OptimizationCUDATritonROCm/HIPXLAQuantization TechniquesBatching TechniquesKV-Cache TechniquesAI Model ArchitecturesCost Modeling

Soft Skills

CollaborationInfluencingResearch Translation

Tools & Technologies

VLLMSGLangTensorRT-LLMAI Model TechnologiesData Center Infrastructure

Industry Keywords

Data Center InfrastructurePower StrategyCooling TopologyVendor Reference DesignsColocation ProvidersHigh-Density Rack DeploymentCommissioningCapacity PlanningEmerging AI TechnologiesU.S. Export-Control Screening

About the role

Key responsibilities & impact

Hold the company's view of the future direction of data center infrastructure
Track vendor and hyperscaler roadmaps, research, standards work, startup and venture landscapes across power, cooling, construction, rack and hall architecture, siting, regulation, and infrastructure economics
Formulate and validate product and engineering theses about what to build, buy, or partner for
Pressure-test technology positions against cost, schedule, and physical plant constraints
Own the technical reference view of client halls across GPU generations, including density, power envelope, cooling topology, and site capacity
Visit operating and prospective sites
Influence cost models for finance, pricing, and sales, including cost per rack, MW, and GPU-hour
Support sales and delivery in technically demanding customer and partner conversations
Provide product and go-to-market guidance on credible capabilities and timelines
Conduct technical diligence on infrastructure partners, colocation providers, vendor reference designs, and prospective tuck-in targets
Validate power strategy, including interconnect availability, queue position, utility and PPA structures, on-site generation, long-lead equipment, site selection, and build sequencing
Collaborate with engineering, product, infrastructure, finance, and commercial teams as a senior individual contributor

Requirements

What you’ll need

Significant hands-on experience with modern AI models
Depth in inference rather than training alone
Working fluency in one or more accelerator ecosystems
Hands-on depth at the compiler, kernel, or runtime layer, such as CUDA, Triton, ROCm/HIP, XLA, or similar
Working fluency in more than one silicon ecosystem
Significant experience working with AI, machine learning, or AI model technologies
Strong understanding of AI model architectures and how models are developed
Ability to understand research and engineering implications of emerging AI technologies
Experience with one or more major model types, such as language, vision, audio, or multimodal models
Hands-on depth in inference, including serving, optimization, and reducing latency and cost while preserving quality
Working knowledge of a modern serving stack such as vLLM, SGLang, TensorRT-LLM, or equivalent
Production knowledge of quantization, batching, and KV-cache techniques
Ability to reason quantitatively about cost to serve and build models that withstand finance and commercial scrutiny
U.S. work authorization required
Visa sponsorship is not currently available
Candidate eligibility may be subject to U.S. export-control screening and, where applicable, licensing
Willingness and ability to travel internationally as needed, up to 25%
Preferred: fluency with frontier labs, open-weight model providers, serving and inference startups, silicon vendors, and relevant research groups
Preferred: applied research experience using primary sources, papers, model cards, vendor roadmaps, or benchmarking to produce defensible positions under uncertainty
Preferred: ability to translate research for engineering, product, go-to-market, and finance
Preferred: experience across multiple data center builds and vendor reference designs
Preferred: liquid cooling or high-density rack deployment experience above 100 kW
Preferred: commissioning, capacity planning, or handover experience for new data center halls
Preferred: publications, patents, standards-body participation, or visible external infrastructure presence
A PhD in a relevant field is described as one valid route but is not required

Benefits

Comp & perks

Approximately three days per week in the office
Willingness and ability to travel internationally to data centers and co-locations (up to 25%)
High-impact technical role with direct influence on AI infrastructure direction
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
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
Lean, senior environment with experienced technical contributors