Top AI & Machine Learning Jobs in Seattle, WA

Serve as the named technical partner for net-new and existing customers, driving adoption and expansion across CoreWeave's AI platform. Work hands-on with customers to train, fine-tune, evaluate, deploy, and scale LLMs and AI workloads, remove technical blockers, deliver demos/POCs, and liaise with Sales, Product, and Engineering to ensure production success and surface product feedback.

The Senior Software Engineer II, AI/ML leads designs, enhances architecture, optimizes multilayer systems, mentors engineers, and ensures service reliability at CoreWeave.

Develop and run rigorous benchmarks and profiles for LLM inference workloads to identify bottlenecks and drive targeted performance optimizations across frameworks, runtimes, and GPU hardware. Design experiments (quantization, caching, speculative decoding), validate changes against real traces, partner with platform engineers to productionize improvements, and produce clear technical writeups to guide model-serving, runtime, and hardware decisions.

Lead and grow the engineering team productizing and operating an inference offering. Drive roadmap execution with Product, improve reliability, observability, release and incident processes, integrate platform capabilities, and deliver developer-friendly tooling and application-layer enhancements to scale production ML workloads.

Lead go-to-market and technical strategy for AI developer tooling, winning early customers and building repeatable playbooks. Translate customer MLOps requirements into product feedback, partner with engineering and Weights & Biases, and enable sales/solutions teams to close deals around experiment tracking, model governance, and LLM observability.

Lead cross-functional programs for inference platform delivery, customer onboarding, launch readiness, and runtime optimization. Drive roadmap outcomes for latency, throughput, uptime, and price-performance. Build metrics, dashboards, launch gates, and repeatable processes for release validation, performance regression tracking, and postmortems. Align Engineering, Product, Infrastructure, and GTM teams to deliver reliable, scalable inference services and operational excellence.

Lead cross-functional programs to validate and optimize AI/ML infrastructure performance. Drive benchmarking, observability, hardware bring-up, release readiness, and measurable metrics across GPU-based clusters. Coordinate engineering, infrastructure, product, capacity, and go-to-market teams to operationalize benchmarking frameworks, prioritize performance work, and ensure platforms meet stability and performance standards for training and inference workloads.

Sell and shape adoption of CoreWeaves AI Runtime Services by driving technical-commercial strategy, proving value with early customers, creating playbooks, and feeding product roadmap. Advise on serving frameworks, batching, execution isolation, throughput modeling, GPU utilization, and SLA structures while partnering with product, infra, and sales teams.

Join a small Applied Training team building Kubernetes-native research cluster and sandbox infrastructure for large-scale ML training. Design and implement cluster experiences (CLI, job schemas, operators), own Python SDKs for RL rollouts, work directly with customers and infra teams, document OSS training frameworks, and ship production-grade ML infrastructure solving distribution, scheduling, and isolation at scale.

The Director of Developer Relations leads the strategy for engaging developers around CoreWeave's AI SaaS offerings, creating content, fostering community, and improving the onboarding experience.