Top AI & Machine Learning Jobs in Seattle, WA

Design and build a greenfield product that reasons over large-scale data with agentic, LLM-backed systems. Architect high-throughput distributed systems, take AI prototypes to production, ensure reliability, cost and correctness, design safety guardrails for autonomous reasoning, and set engineering standards for quality, testing, and observability.

The role involves architecting AI applications, delivering scalable solutions, conducting research, and implementing high-quality code for cloud platforms. Requires collaboration and effective communication.

Design, build, and operate agentic AI systems end-to-end for Professional Services. Translate stakeholder needs into secure, scalable multi-agent architectures, define performance benchmarks, manage deployments and incident response, advise leadership, mentor teammates, and maintain runbooks and production tooling including on-call responsibilities.

Design, build, and operate large-scale LLM infrastructure and data platforms for training, fine-tuning, and inference. Provision GPU clusters, optimize GPU utilization, implement model lifecycle management, deploy inference frameworks, create evaluation and observability systems, and collaborate with data scientists to productionize AI capabilities. Mentor engineers and enforce MLOps/DataOps best practices.

Build and scale AI platform infrastructure for internal agents across AWS/GCP. Integrate identity (Okta, OAuth2/OIDC), implement agentic security, containerized deployments (Docker/Kubernetes), CI/CD and Terraform-based pipelines, run vendor evaluations, and design observability/telemetry for LLM-driven workflows while collaborating with security, identity, and engineering teams.

Design, build, deploy, and iterate production-ready AI agents and LLM-based solutions that integrate with enterprise workflows. Rapidly prototype, evaluate, and optimize agents for performance, cost, and adoption. Partner across functions to redesign workflows, contribute to an AI Center of Excellence, and ensure responsible, secure, and scalable agent development.

As a Principal Data Engineer, you will design and implement LLM, AI-powered security data platforms, mentor engineers, and drive the adoption of data solutions across teams.

Design, build, and productionize machine learning models to attribute cloud costs, forecast usage, and detect anomalies. Analyze large-scale cloud and financial datasets, run experiments, collaborate with engineers to deploy and monitor models, and report project status while improving team technical capability.

Lead AI strategy, partner engagements, and operational execution across CrowdStrike products. Align R&D and product delivery to company AI strategy, prioritize initiatives, set organizational goals, drive thought leadership, and create order in complex cybersecurity AI environments while delivering customer value.

Lead research and engineering of production-grade LLM/GenAI systems for cybersecurity: design models and architectures, drive data labeling and evaluation, collaborate with product and engineering to deploy scalable solutions, mentor data scientists, set technical strategy, and advance AI safety, red-teaming, and applied ML innovations for detection and operational use.