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

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 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.

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

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.

Design and deliver full-stack features for AI voice and chat products at enterprise scale. Integrate ASR/TTS and LLM improvements, optimize production systems for latency and cost, participate in on-call rotations, and collaborate with product and ML teams to ship high-impact, scalable solutions.

Lead and grow a team of Conversation Designers to build and scale conversational AI experiences. Partner with Product, Engineering, Analytics, and ML teams to drive strategy, tooling, evaluation, and quality practices. Recruit and remove roadblocks, own strategic initiatives, and remain hands-on in designing, testing, and improving AI-driven conversational products.

Build full-stack features for enterprise-scale voice and chat AI: integrate ASR/TTS and conversational LLMs, optimize production systems for latency and cost, participate in on-call rotations, and collaborate with product and ML teams to ship high-impact, scalable solutions.

Perform text and image annotation tasks in Turkish: review content, draw bounding boxes, answer structured questions, write short summaries, and follow annotation guidelines to ensure quality. Remote, long-term (minimum 6 months) role with provided training and a short language assessment.

Evaluate a personalization feature for Gemini by designing multi-turn prompts using personal data, comparing side-by-side model responses, assessing grounding, integration, and helpfulness, writing clear rationales, extracting debug info, and maintaining strict data hygiene.

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.

Lead architecture and productionization of NLP, voice, and ML systems; mentor engineers; integrate AI features with backend services on AWS; build evaluation, monitoring, and responsible-AI safeguards; drive AI strategy and technical vision.

Translate and localize content between English and Hebrew, edit for accuracy and tone, apply language standards, provide feedback to improve language model quality, collaborate with production teams, support localization and QA for digital tools, and perform creative transcreation when required.