Top Natural Language Processing (NLP) Jobs in Boston, MA

Build and maintain real-time transcription and LLM-powered summarization pipelines, contribute to agentic tool-calling systems and integrations, develop full-stack services (Node.js/TypeScript, React, PostgreSQL) on AWS, support event-driven architectures, collaborate on prompt engineering, and ensure reliability, observability, and testability of production AI systems.

Assist in designing high quality AI conversation models for customer contact centers. Collaborate with teams to build solutions that meet business objectives and maintain AI model quality.

As a Lead Data Engineer, you'll design and implement AI-powered data systems, focusing on natural language queries and scalable frameworks. Collaborate with teams to optimize data access and enhance reporting tools.

Design, build, and deploy AI-driven documentation and localization systems (TMS/CMS), improve translation memory and automation, support DITA/XML workflows, develop Python scripts for publishing, and implement generative AI/NLP solutions within a regulated life-sciences environment.

The role involves designing and building AI components for a platform, specifically focusing on NLP and ML for catalog mapping and anomaly detection, along with feedback mechanisms.

The Research Engineer III will build and maintain ML infrastructure, develop NLP models, implement tracking integrations, and ensure observability in ML pipelines.

Own strategy, roadmap, and execution for client-facing analytics and AI insights. Deliver dashboards, reports, and conversational NLQ analytics. Partner with data engineering, data science, and platform teams to shape semantic models and LLM-backed analytics. Drive adoption with Sales, Customer Success, and Implementation teams and use AI tools to accelerate product work.

Lead design of AI agent experiences—conversation and voice flows, multi-turn dialogs, escalation and error handling. Create user journeys, information architecture, wireframes, and clickable prototypes. Co-facilitate discovery workshops, ground decisions in user research, contribute to design systems, and ensure scalable, production-ready UX patterns for enterprise AI deployments.

Build and deploy NLP solutions: perform EDA on text, design and evaluate models (classification, NER, information extraction), develop pipelines from regex to transformers, apply generative AI and prompt engineering, write production-grade Python, and collaborate with ML engineering to deploy and monitor scalable cloud-based solutions.

Lead a development team to design, build, and maintain conversational AI solutions on the Kore.AI platform. Architect scalable chatbots, implement NLP/NLU, integrate cloud and CI/CD pipelines, perform code reviews, troubleshoot issues, and provide technical leadership and mentoring across cross-functional teams.