Top Natural Language Processing (NLP) Jobs in Seattle, WA

Lead design and delivery of conversational and agentic AI solutions for client contact centers. Guide cross-functional teams to build NLP interfaces, prototype UIs, run usability testing, ensure data integrity and security, and advise clients strategically. Coach teams, manage large projects, and drive adoption of AI-powered contact center technologies to improve client experience and operational outcomes.

Lead product vision, strategy, and execution for Rovo Chat, Atlassian's AI-driven conversational interface. Prioritize adoption and quality, drive multi-turn conversation improvements, integrate knowledge across first- and third-party sources, partner cross-functionally to ship features, define success metrics, and champion responsible AI practices for safe, transparent conversational experiences.

Lead end-to-end product for voice protection and conversational AI features serving consumers and telecom operator partners. Define product vision, prioritize roadmap, work closely with engineering and research on model training and prototyping, engage customers to validate needs, support commercial and legal partners, and drive product economics and successful launches.

Lead design of zero-to-one conversational experiences across LLMs, messaging apps, and voice/chat interfaces. Collaborate with PMs, engineers, researchers, and content to define requirements, craft scalable flows, and evolve a shared conversational platform and design system to ensure consistent, accessible experiences.

Lead end-to-end delivery of document extraction and NLP solutions for payments: design scalable model pipelines, develop extraction/classification models, define evaluation and lifecycle practices, ensure compliance and explainability, and partner with cross-functional stakeholders to productionize and monitor ML systems.

The Staff Machine Learning Engineer will lead ML initiatives, partnering with multiple teams to enhance customer support through AI-driven solutions, focusing on conversational agents and research in chatbot architectures.

Research, develop, and productize scalable AI/ML and GenAI solutions (LLMs, NLP, agentic systems). Build, evaluate, optimize, and deploy deep learning models, collaborate with engineers and product teams, publish research, and contribute to Conversational AI and data science roadmaps.

Design and build scalable, high-performance conversational search features using React and Java integrated with LLMs. Lead multi-person projects, balance infrastructure and pragmatic solutions, mentor engineers, evaluate AI tools/models, collaborate with product/design, and participate in on-call rotation to ensure reliability and performance.

Design and implement scalable, secure inference services for speech processing. Optimize networking, audio transcoding, latency, memory, and distributed compute orchestration. Debug complex system issues, customize backend services for customers, and partner with Product to deliver end-to-end features.

Lead end-to-end performance of customer-facing conversational AI and knowledge base. Design, test, and optimize AI conversations, define intents and success metrics, analyze KPIs, maintain enterprise knowledge, run continuous improvement using analytics and experimentation, and partner cross-functionally to improve CX and business outcomes.