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

Extract structured facts from long, unstructured and semi-structured documents while preserving exact source citations. Validate evidence, distinguish stated totals from derived calculations, handle ambiguity without guessing, and apply established extraction methods consistently. Collaborate with entity resolution and retrieval teams to support downstream systems. The role requires strong Python and NLP or information-extraction experience, U.S. citizenship, and an active Secret clearance.

Participate in a one-time, remote guided English voice recording session (~20 minutes) using your own compatible device. Must follow recording instructions, complete session in a quiet indoor environment, be at least 18, reside and record from an approved U.S. state, and submit one participation only. Approved participants who meet quality standards receive $25.

Design, develop, and deploy ML, NLP, and generative AI solutions to improve scientific discovery. Build retrieval, recommendation, ranking, and RAG systems; fine-tune and evaluate LLMs; create evaluation frameworks; build scalable data pipelines; collaborate with cross-functional teams and produce production-quality Python code to deliver reliable, impactful AI systems for research use.

Build and productionize large-scale TTS and adjacent speech models end-to-end: model architecture, training, alignment, evaluation, data curation, distributed GPU scaling, latency/cost profiling, tooling, and safety/mitigation for speech systems.

Design and implement AI/NLP solutions to automate insurance policy administration (issuance, endorsements, renewals). Translate policy language into models and rule engines, integrate with PAS, ensure regulatory compliance, monitor model performance, and support underwriting, operations, and exception handling.

The Senior AI/ML Engineer will design, develop, and deploy language models for African languages, focusing on NLP applications and cultural context.

Perform language- and culture-sensitive human review and annotation of AI outputs across text, audio, and video. Generate or assess content, identify errors and cultural mismatches, provide structured annotations, and follow evaluation guidelines and QA calibration to improve models.

Lead enterprise strategy and product management to scale AI-powered voice, chat, email, and conversational experiences. Own roadmap, platform modernization, global deployment, governance, and continuous optimization to increase digital adoption, reduce servicing demand, and deliver measurable business value across servicing operations.

Own the end-to-end vision and roadmap for Boulevard's AI Receptionist. Define how AI handles voice and text client interactions, design handoffs to humans, set success metrics (autonomous resolution, CSAT, adoption, retention), drive business outcomes and pricing, gather deep customer insight from self-care businesses, and lead cross-functional teams to deliver trustworthy, high-quality AI conversational experiences.

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.