Top Natural Language Processing (NLP) Jobs in Chicago, IL

Lead design, development, and productionization of ML and LLM/NLP systems. Own feature engineering, model evaluation, monitoring, and bias analysis. Partner with Product and Engineering to drive operational impact and act as senior technical owner and reviewer for data science work.

The Staff AI Software Engineer will own the full AI systems lifecycle, from model development to production deployment, focusing on NLP and generative AI solutions, while collaborating with cross-functional teams to optimize and drive solutions.

Design, train, and implement domain-specific LLMs for automation in restoration companies. Collaborate with teams, coordinate AI engineering, and ensure model reliability.

Lead the design and delivery of scalable voice and chat solutions using Amazon Connect, focusing on integrations, reliability, and performance optimization.

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.

Lead end-to-end development of an AI platform that automates customer interactions using LLMs, agents, APIs and human-in-the-loop feedback. Define prompt strategies, evaluation frameworks, guardrails, and metrics; partner with engineers and OpenAI to deploy voice and automation models; drive experiments to improve quality, satisfaction, and automation rates.

Design and build AI agent systems, focusing on LLM applications and autonomous workflows. Requires expertise in AI integration and Python development.

As a Sr AI Enterprise Engineer, you'll design and deploy intelligent systems using large language models, build conversational agents, and support teams in AI enablement while driving collaboration and innovation across the company.

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.

The AI/Machine Learning Engineer will develop systems for automating health benefits decisions, integrating large language models with rule-driven patterns, and ensuring compliance with regulations.