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

Freelance PhD-level Brazilian Portuguese expert will create challenging, original literature and linguistics questions and model answers for AI training, breaking responses into cited factual segments. Work supports NLP training data; AI tools allowed only for research support. ~60 flexible hours over two months.

The Principal LLM Application Engineer will develop and optimize Large Language Models, lead projects, evaluate performance, and collaborate across teams to enhance AI capabilities in cybersecurity.

As an AI Conversation Designer, you'll create and optimize chatbot flows, analyze performance, and collaborate cross-functionally to enhance customer interactions using AI and NLP technologies.

Review and annotate Korean text and images (bounding boxes, structured questions, short summaries) following annotation guidelines to train AI systems. Work remote, 30-40 hrs/week for at least 3 months; on-the-job training provided.

Train and fine-tune large language models, build and maintain the full LLM stack and agentic pipelines, improve chat/agent algorithms, translate NLP research into roadmap, and collaborate with validation, content, and dataset teams to design experiments and measure model quality.

Lead Conversational AI Developer responsible for developing chatbots and virtual assistants, integrating AI technologies, and improving user interactions through data analysis and software development.

The Senior Data Scientist in Conversational AI & NLU designs and optimizes AI solutions, evaluates models, collaborates with stakeholders, and analyzes conversational data to improve user experience.

The Senior AI Engineer will develop AI-driven solutions using LLMs, focusing on prompt engineering, integration, research, and data utilization for payment systems.

Design, develop, and optimize scalable data systems and pipelines focused on knowledge graph construction, curation, and semantic representations. Build RDF/SPARQL-based graphs, apply ontology-driven modeling and NLP techniques to enable AI reasoning, and collaborate in a hybrid team to support knowledge generation, transformation, and analysis.

Develop and deploy AI-powered chatbot applications, design conversational flows, integrate with various platforms, and optimize performance.