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

The role involves developing AI systems for processing voice data, optimizing ML workflows, and collaborating on ML and LLM solutions.

Design and build scalable, permission-aware retrieval and reasoning systems for Zoom's AI Companion: vector and hybrid search, RAG pipelines for agentic reasoning, ranking and evaluation frameworks, indexing and NLP/entity extraction pipelines, and collaborate with product, infrastructure, and research to ship production-grade LLM-based features.

Lead and execute research on large language models and agentic systems, running large-scale post-training experiments (SFT, RLHF, RLAIF, DPO, GRPO), building evaluation benchmarks and data synthesis pipelines, translating research into model improvements and production deployments, publishing at top venues, and mentoring researchers and engineers.

Design, evaluate, and deploy LLM-powered features end-to-end: prompt engineering, semantic retrieval, embeddings, vector stores, evaluation frameworks, and production integration while collaborating with product and engineering and working directly with users.

The role involves developing and deploying large language models for healthcare, applying advanced ML techniques, and collaborating with interdisciplinary teams.

Develop intent-recognition models from gaze, gesture, and voice data; implement socially aware navigation that respects personal space; and design visual and auditory feedback for robot user interfaces. Run user studies and rapidly prototype AI-driven voice and visual interfaces.

Evaluate and rewrite AI-generated Ukrainian text for accuracy, grammar, and cultural relevance. Create prompts and natural Ukrainian responses, perform structured ranking and grammatical checks, and collaborate with global teams to improve conversational datasets. Freelance, remote, ~10 hours/week for 1-2 months.

The Research Engineer will design and implement scalable machine learning systems for next-gen language models, optimizing training and inference processes, while working collaboratively and contributing to open-source projects.

Build and maintain real-time transcription and LLM-powered summarization pipelines, contribute to agentic tool-calling systems and integrations, develop full-stack services (Node.js/TypeScript, React, PostgreSQL) on AWS, support event-driven architectures, collaborate on prompt engineering, and ensure reliability, observability, and testability of production AI systems.

Assist in designing high quality AI conversation models for customer contact centers. Collaborate with teams to build solutions that meet business objectives and maintain AI model quality.