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.

Lead onboarding and roadmap for integrating conversational AI into an enterprise QA platform. Design automated AI QA, evaluation pipelines, and closed-loop feedback systems to scale consistent, accurate assessments across complex customer intents.

Own monitoring, testing, and tuning of Inspira's AI virtual agent to improve resolution, deflection, and CSAT. Analyze conversation transcripts and performance data, run A/B and regression tests, adjust retrieval/configuration and intents, partner with Content and IT to fix knowledge gaps, maintain performance dashboards, lead root-cause analysis, and support go-lives for new bot capabilities.

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.

Lead end-to-end performance of customer-facing conversational AI and knowledge base. Design, test, and optimize AI conversations, define intents and success metrics, analyze KPIs, maintain enterprise knowledge, run continuous improvement using analytics and experimentation, and partner cross-functionally to improve CX and business outcomes.

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.

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.

Lead and grow a data science team to design, prototype, and productionize NLP/LLM systems for legal content. Set AI strategy, build evaluation and monitoring, drive RAG/agentic solutions, collaborate cross-functionally, and ensure scalable, reliable deployment and responsible use of generative AI.

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.