Top Tech Jobs & Startup Jobs in Seattle, WA

Design and build monitoring, telemetry, and data pipelines to operate flagship supercomputers at scale. Diagnose and troubleshoot GPU hardware, networking, datacenter and software stack issues, implement systemic mitigations, improve observability, and drive reliability and performance improvements through incident reviews and tooling.

Operate and improve large-scale HPC GPU clusters for AI model training and inference. Build observability, automation, CI/CD, and incident response tooling; lead on-call rotations, ensure security/compliance, collaborate with ML engineers, and optimize capacity and costs for production ML workloads.

Lead hardware-software co-design for datacenter-scale AI systems, analyzing real workloads to drive architecture, performance, and cost improvements; prototype and productionize optimizations across accelerators, runtimes, compilers, interconnects, and distributed training/inference; mentor engineers and influence hardware and platform roadmaps.

Design, develop, and operate monitoring and observability solutions for flagship supercomputers. Build data pipelines to process large telemetry and logs, respond to incidents, implement mitigations, write postmortems, and improve reliability, performance, and operational runbooks at scale.

Design, build, and manage low-latency, high-performance networking infrastructure for large-scale AI training in Azure. Test and validate devices and firmware, automate deployments, monitor telemetry, troubleshoot live site incidents, participate in on-call duties, and guide datacenter staff on secure hardware operations.

Build and maintain a capacity management portal and observability features for ML training and inference. Partner with researchers and PMs to turn requirements into intuitive UIs, integrate backend APIs across schedulers and training frameworks, develop internal tooling, and drive architectural improvements and best practices to improve efficiency and model quality visibility.

Lead and grow a developer experience team responsible for monorepo strategy, CI/CD, build systems, developer environments, and onboarding. Improve engineering velocity, CI reliability, and developer trust; establish standards, adopt AI-assisted workflows, and partner with infra/ML teams to remove friction for large-scale AI research.

Technical pre-sales role designing secure, scalable Azure architectures and migrations. Lead workshops, demos, and proofs-of-concept; guide modernization (6R, containerization, AKS, Arc); design hybrid networking and enterprise integrations; collaborate with engineering and partners to remove technical blockers and meet security and compliance requirements.

Lead customer-facing Azure cloud and AI architecture engagements: advise executives, design secure scalable solutions, drive Azure adoption, modernize applications, and enable production-scale AI across apps, infra, and data while mentoring peers and delivering technical excellence.

Design and deliver secure, scalable Azure and AI-ready infrastructure. Lead architecture sessions, drive migrations and modernization (infrastructure, databases, SAP, hybrid), ensure operational excellence, create repeatable IP, resolve technical blockers, and accelerate customer adoption and business value.