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

Design and build responsive, resilient conversational search experiences using React, Java, and AI technologies. Lead multi-person projects, mentor engineers, collaborate with product, evaluate LLM tools and frameworks, ensure performance and reliability, and participate in on-call rotation to support production systems.

Lead creation of purpose-built large language models for Cisco's networking, security, data center, and observability domains. Drive end-to-end pre-training, distillation, and continual pre-training efforts, curate datasets and tokenization strategies, train models on large distributed GPU clusters, publish top-tier research, and collaborate with cross-functional teams to deploy research into scalable product solutions.

Lead design and strategy for AI-driven conversational experiences: build conversation architectures, response patterns, structured content models, and interaction frameworks. Partner with Product, UX, Engineering, and ML teams to ensure explainable, controllable AI behavior, optimize via research and analytics, run cross-functional workshops, and mentor other designers to scale conversation design across the enterprise.

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

Assess English-language content for clarity, coherence, accuracy, and guideline adherence; perform long-form text evaluations consistently; document findings; work independently within a team and maintain high quality on repetitive tasks.

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, develop, and deploy machine learning and NLP solutions at scale. Work with cross-functional teams to build content classification, representation learning, search, and recommendation models using classical ML, deep learning, and LLMs. Process large datasets with Python, SQL, and Spark, and communicate results to stakeholders with clear documentation.

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.

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

Review, localize, fact-check, translate, and adapt football-related content (EN→FR-CA). Conduct market research on terminology and trends, provide copy-editing and feedback, and evaluate/MTPE machine translations to ensure native-level quality and adherence to style guides.