Top Natural Language Processing (NLP) Jobs in Denver & Boulder, CO

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.

Own and evolve revenue calibration models tying CX interactions to revenue, design causal inference and experimentation frameworks, build LLM-powered classification/NLP pipelines, productionize models with Analytics Engineers, define segmentation and behavioral signals, and ensure statistical rigor for executive reporting and regulatory defensibility.

Design and implement Vercel's agentic interface and agent architecture to understand intent, plan workflows, select tools, recover from failures, and execute long-running tasks. Ship polished conversational and interactive experiences across Slack, web, and other surfaces. Build evaluation, observability, and feedback systems and primitives enabling teams to contribute consistent agent capabilities across the company.

Own end-to-end voice platform migration and scaling: LiveKit migration, real-time turn-taking, VAD, SIP/WebRTC, multi-agent handoff, training/fine-tuning voice models, inference cost optimization, and retrieval-based grounding using Supabase/pgvector.

Design and implement conversational and agentic AI solutions, build natural language interfaces and voice experiences, prototype UIs, conduct user research and usability testing, integrate AI platforms into contact center systems, and collaborate with cross-functional teams to optimize user interaction engineering and client outcomes.

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.

Summer internship working on transformer-based models to automate scoring of Spanish constructed responses. Collaborate with psychometricians and data scientists to design experiments, implement models in Python, evaluate with industry metrics (QWK, accuracy, SMD), and document and present findings.

Review and evaluate AI-generated responses, annotate and validate text/conversations, identify linguistic and contextual issues, and ensure annotations meet quality and linguistic guidelines to improve LLM performance.

Build and maintain full-stack, AI-native features for Cross River's data platform, including React UIs, Python APIs, LLM-powered agents, RAG, and natural-language-to-SQL experiences. Ensure secure, auditable model integration, data governance, and operational stability while collaborating across engineering and data teams.

Lead design, research, and productionization of advanced NLP and LLM systems (NER, classification, generation, RAG/GraphRAG, semantic search). Drive experiments, model evaluation, data labeling strategy, and integration of NLP models into production workflows while providing technical leadership across engineering, product, and data teams.