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

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.

Design, build, and deploy ML and AI systems at scale for content classification, recommendations, search, and metadata enrichment. Work with cross-functional teams to process large datasets, develop models from classical NLP to LLMs, implement production pipelines, and communicate results to stakeholders.

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.

Design, develop, validate, and deploy ML and NLP models (including LLMs/Generative AI) for payments and credit analytics. Analyze multi-terabyte datasets, perform statistical testing and feature engineering, document models, build dashboards, and collaborate with stakeholders to remediate model issues and drive AI/ML innovation.

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 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.

Lead a team to develop groundbreaking technology combining NLP, big data, and AI to enhance digital communication and interaction.

As a Principal Scientist, you will guide the machine learning team in developing natural language applications, focusing on automated scoring and feedback systems. You'll contribute to R&D efforts, support innovation in EdTech, mentor team members, and pursue applied research.