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

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

Design and implement scalable, secure inference services for speech processing. Optimize networking, audio transcoding, latency, memory, and distributed compute orchestration. Debug complex system issues, customize backend services for customers, and partner with Product to deliver end-to-end features.

Design and deliver LLM-powered, agentic AI systems to automate customer support and compliance. Build scalable, secure backend infrastructure in Python and Go, integrate third-party models/APIs, implement grounding and guardrails, and measure performance. Lead end-to-end projects, mentor engineers, conduct code reviews, and participate in on-call and incident response to improve resolution times and reduce operational costs.

Build and own conversational voice AI products end-to-end: architect, implement, and deploy the platform. Design infrastructure, develop front-end and back-end systems, deliver reliable customer outcomes, and collaborate directly with the CTO to scale the product for enterprise customers.

Design, build, and deploy production-grade ML models and scalable pipelines (training, inference, monitoring) using NLP/LLM, classification, recommendation, and prediction techniques. Collaborate with product and engineering, optimize latency and costs, and implement retraining and observability for healthcare workflow automation.

Own the end-to-end customer-facing conversational agent across chat and voice. Set roadmap, drive conversation and interface design in Figma, prototype with AI coding tools, define agent behavior and quality metrics, partner with enterprise clients for requirements and launches, and iterate from production conversation data.

Design, develop, and deploy machine learning and NLP solutions at scale. Work with cross-functional teams to build content classification, representation learning, search, and recommendation models using classical ML, deep learning, and LLMs. Process large datasets with Python, SQL, and Spark, and communicate results to stakeholders with clear documentation.

Build, productionize, and operate AI-driven features and integrations across frontend, backend, and model layers. Prototype and deliver agent-driven experiences (conversational interfaces, RAG, tool-calling), integrate LLMs and external data sources, and collaborate with product and design. Participate in on-call/standby duties.

Record natural, conversational customer-service style speech from a home studio. Submit two audition samples; if selected, complete two supervised ~4-hour remote recording sessions meeting technical audio specs.

Reviews written content and AI-generated responses for accuracy, clarity, grammar, coherence, completeness, and guideline adherence. Provides concise, constructive feedback, identifies subtle linguistic errors, documents findings using evaluation tools, and consistently applies evaluation criteria during a four-week remote contract sprint requiring at least 20 hours per week.