Top AI & Machine Learning Jobs in Seattle, WA

The Staff Forward Deployed Engineer drives AI adoption for strategic customers by solving complex cloud infrastructure challenges, developing scalable assets, and influencing product roadmaps through collaboration and technical expertise.

Lead design and implementation of scalable, multi-tenant serverless inference services focused on throughput, GPU utilization, resiliency, observability, and operational tooling. Partner with platform and GPU teams, debug production performance issues, mentor engineers, drive incident response, and create reusable patterns, standards, and automation for inference workloads.

Lead design, build, and operate high-scale, resilient inference data plane services for LLMs. Drive distributed system architecture, performance optimization (tensor/data parallelism, KV-cache routing), Kubernetes-native serving frameworks, open-source contributions, mentorship, and production SLO-driven operations to deliver Inference-as-a-Service with low latency and high availability.

Lead applied research and engineering for feedback-driven agentic AI: define reward modeling and reinforcement learning roadmap, design production learning loops and evaluation frameworks, run large-scale experiments, and ship research into production while partnering across product and engineering.

Own product strategy and roadmap for managed agent infrastructure. Define services (harness server, sandbox, gateways), partner with customers and engineering, shape developer experiences, launch products, and drive adoption, reliability, and revenue metrics.

Lead the strategy and execution for DigitalOcean's agentic AI infrastructure: design and scale runtimes, sandboxed execution, tool and state management, launch revenue-driving SKUs, optimize efficiency and margins, and build a high-performing distributed engineering organization focused on reliability and operational excellence.

Lead applied research and technical direction for agent memory in production AI: define roadmap, design and build memory and retrieval architectures, run large-scale experiments, develop evaluation frameworks, and partner cross-functionally to ship reliable, personalized long-running agent capabilities.

Lead multi-year product strategy and roadmap for DigitalOcean's Data and AI platform. Own development of vector databases, knowledge bases, Iceberg-supported data primitives, and integrations for RAG and AI agents. Drive cross-functional execution, pricing, capacity planning, and customer-driven feature prioritization; measure utilization, reliability, and deployment velocity.

Design, build, and operate the Action Runtime execution layer for AI agents. Own full-stack product features from design through production, including MCP tooling, authentication, secrets, rate limiting, observability, and safe execution. Collaborate with product, design, and cross-functional teams, mentor peers, participate in on-call, lead incident responses, and define quality standards, evaluations, and telemetry for reliable agent tooling.

Lead strategic partnerships for DigitalOcean's AI-Native Cloud, focusing on agentic AI products. Identify and qualify partners, negotiate complex commercial deals (OEM, revenue share), coordinate cross-functional evaluation and integration, and transition partnerships to Product and GTM teams to drive platform innovation and partner-driven product features.