Top AI Research Jobs in Seattle, WA

Conduct research in user modeling and personalization, including graph modeling, generative recommendation, personalization, and ML efficiency. Lead research projects, build scalable prototypes, evaluate large-scale machine learning systems, and publish findings at top conferences. The role also involves mentoring interns and junior researchers and translating advanced research into product improvements.

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.

Lead development of a Semantic Brain: map raw event logs to industry ontologies, build concept/identity-anchored graphs, design reward extraction and off-policy evaluation, deploy agentic LLM orchestration and scalable data pipelines to enable autonomous enterprise decisioning.

Own Deepgram’s end-to-end text-to-speech research program, including technical strategy, model architectures, experiments, training, evaluation, and production deployment. Lead researchers and technical managers, establish roadmaps, advance naturalness, expressiveness, multilingual generation, controllability, voice consistency, and inference efficiency, and partner with engineering and product leadership to ship high-quality models.

Manage and coach a team of mentors to ensure delivery outcomes for ~200 AI fellows at scale. Build delivery systems, run operational cadence, lead live instruction when needed, translate field signals into curriculum changes, and partner with strategic partners to close the feedback loop between mentors, fellows, and the curriculum team.

Lead development and large-scale training of foundation models across pretraining, fine-tuning, and post-training. Design experiments and evaluations, diagnose training failures, improve model quality, scale methods on GPU clusters, and provide technical direction and mentorship across research and engineering teams.

Conduct applied AI research in computer vision, machine learning, generative AI, and multimodal systems. Lead research from proof of concept through production, developing responsible and privacy-preserving models for visual data. Create metrics, optimize models for resource-constrained devices, validate performance, collaborate with scientists, engineers, and product managers, and contribute to publications, technical documentation, and patents.

Design and research agentic AI and reinforcement learning systems: build auto-research and coding agents, develop recursive self-improvement and multi-agent frameworks, run RL experiments (RLHF, DPO, PPO), curate training data pipelines, and publish results at top ML venues.

Invent and evaluate novel AI/ML methods for large-scale biological data. Design experiments, benchmarks, and reusable modeling frameworks; collaborate with scientists and engineers; publish and share methods to advance scientific discovery.

Define Cisco’s multi-year AI research strategy and architecture for purpose-built large language models in networking, security, data center, and observability. Lead massive-scale pre-training, continual pre-training, reinforcement learning, alignment, agentic framework, and autonomous operations initiatives. Advise executive leadership on production-scale AI ecosystems, publish influential research, lead academic initiatives, and mentor senior research talent.