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

Design, build, and deploy AI-powered conversational voice solutions using LLMs and Amazon Bedrock. Integrate and fine-tune models, develop scalable cloud services and APIs, apply DevOps/CI-CD practices, collaborate cross-functionally, and monitor/optimize voice bot performance with an emphasis on responsible AI.

Design, build, and scale an AI-native conversational platform powering autonomous customer agents. Own full-stack systems, retrieval and orchestration, observability, and multi-channel experiences. Lead technical decisions, mentor engineers, and deliver reliable, tested, customer-facing features that enable brands to launch and improve configurable AI agents.

The role involves partnering with cross-functional teams to design, develop, and deploy AI software solutions, focusing on large language models and AI optimization techniques.

The Research Engineer will collaborate with scientists to develop and validate machine learning models for speech technologies, manage scalable training systems, and design tools for accessibility to non-technical users.

The Senior Data Scientist in Conversational AI & NLU designs and optimizes AI solutions, evaluates models, collaborates with stakeholders, and analyzes conversational data to improve user experience.

The role involves researching and developing training strategies for large language models, focusing on their applications in scientific reasoning and performance evaluation.

Develop intent-recognition models from gaze, gesture, and voice data; implement socially aware navigation algorithms respecting personal space; and design visual and auditory feedback for robot user interfaces. Conduct user studies and rapid prototype AI-driven voice and visual interaction systems to test and refine HRI paradigms.

Lead end-to-end conversational UX for an AI-powered financial assistant: design stateful, multi-turn and multi-session experiences; define memory and re-entry strategies; prototype front-end interactions; translate policies and compliance into intuitive UX; collaborate with product, engineering, AI platform, and risk teams; iterate using user feedback and behavioral signals.

Lead development and scaling of an AI platform that automates inbound sales and service using LLMs and agents. Define roadmap, design prompt strategies, evaluation frameworks, and guardrails. Translate between engineering and business, run experiments to improve quality and automation rates, and partner with OpenAI on model and voice integrations.

As a Research Scientist, you will develop innovative machine learning techniques for clinical applications, design large language models, and collaborate with engineering teams while advancing NLP research.