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

Work across AI, backend, and frontend: curate and clean writing datasets, fine-tune large language models, run training experiments, develop metrics and eval sets, build backend services in Python/Django, and implement frontend features with React.

Develop and iterate post-training methods for large language models: drive data collection, build evaluations, design experiments, and apply reward modeling and RL techniques to improve model capabilities and deployment.

Join Welo Data’s remote Welsh AI contributor network for flexible projects involving text, image, or audio annotation; search, ad, and chatbot evaluation; prompt creation; and linguistic or cultural quality review. Projects vary from several days to weeks, with scope, timelines, and compensation provided before each assignment. This is a talent community application, not an active job opening.

Design real-world ML and NLP tasks, build reference solutions and evaluation frameworks in Python, assess LLM outputs for correctness and reasoning, identify failure modes, create scoring rubrics, and collaborate with experts to improve model capabilities. Part-time, remote contractor (~20 hours/week).

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.

The Senior AI/ML Engineer will design, develop, and deploy language models for African languages, focusing on NLP applications and cultural context.

Perform language- and culture-sensitive human review and annotation of AI outputs across text, audio, and video. Generate or assess content, identify errors and cultural mismatches, provide structured annotations, and follow evaluation guidelines and QA calibration to improve models.

Design, build, and deploy scalable AI/ML models (especially NLP and predictive models), implement MLOps and data pipelines, optimize model performance, research prototypes, ensure ethical and compliant AI, and collaborate with product, engineering, and data teams to embed AI into the leave management platform.

Own post-sale delivery and ongoing performance of credit-union-facing AI agents (Emma): design conversation behavior, run live testing and go-lives, monitor quality and drift, run executive business reviews, codify playbooks and monitoring, and build the operating model and team to scale the function.

Conduct and productize cutting-edge multilingual live caption and translation research. Build and integrate ML/DL models, partner cross-functionally, act as domain expert, and present research across the company to drive localization impact.