Top Natural Language Processing (NLP) Jobs in Austin, TX

Design, build, evaluate, and deploy NLP and LLM systems (classification, extraction, retrieval). Create evaluation frameworks, golden datasets, and annotation guidelines. Analyze performance, identify failure modes, partner with engineering for production deployment and monitoring, and communicate results to stakeholders.

The Research Engineer will collaborate with scientists to develop and validate machine learning models for speech technologies, manage scalable training systems, and design tools for accessibility to non-technical users.

Own and evolve revenue calibration models tying CX interactions to revenue, design causal inference and experimentation frameworks, build LLM-powered classification/NLP pipelines, productionize models with Analytics Engineers, define segmentation and behavioral signals, and ensure statistical rigor for executive reporting and regulatory defensibility.

Design, refine, and evaluate AI-driven conversational agents in production to improve containment, task completion, and patient experience. Analyze interaction data, triage live issues, write and iterate prompts, partner with Product/Engineering/QA, and build frameworks, standards, and training to scale conversational quality across customers and deployments.

As a Senior Customer Experience Consultant, you will design and implement engaging conversational flows for Intelligent Virtual Assistants, ensuring exceptional customer interactions through effective dialogue scripting and collaboration with AI engineers.

The Senior Applied Scientist will research and engineer NLP solutions, design algorithms, train LLMs, and contribute to platform development.

The role involves developing language models for voice systems, analyzing linguistic data, and maintaining existing voice applications at Roku. It requires expertise in linguistics and NLP technologies.

Lead and mentor teams in developing language model-based AI solutions, ensuring high technical standards, quality implementations, and effective communication with stakeholders.

Develop and maintain applications using MCP and ChatGPT frameworks, optimize AI interactions, and prototype innovative solutions. Collaborate on product architecture with minimal supervision.

As a Lead Data Engineer, you'll design and implement AI-powered data systems, focusing on natural language queries and scalable frameworks. Collaborate with teams to optimize data access and enhance reporting tools.