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

Partner with portfolio managers and researchers to design, prototype, and deploy LLM-enabled AI tools that accelerate investment insights. Lead proof-of-concept and production delivery, ensure security, governance, and regulatory compliance, and transition prototypes into scalable enterprise capabilities working across Investments, Technology, Data, Risk, and Compliance.

The Senior Machine Learning Engineer will develop, deploy, and optimize large language models on healthcare data, collaborate with teams, and ensure compliance.

As a Research Engineer/Scientist, advance large-scale language model technologies focusing on pre-training, post-training, and Reinforcement Learning, while collaborating with product managers and engineers to implement impactful AI solutions.

Implement and maintain record-matching and text-analytics components, translate linguistic theory into production features, optimize search internals (Elasticsearch), collaborate in agile sprints, and help design scalable APIs and architectures to improve record-matching quality and reliability.

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.

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.

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

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.

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.

Build and maintain record-matching and text-analytics components for an AI-native analytics platform. Implement NLP and linguistics ideas into production code, optimize search internals (Elasticsearch), collaborate in agile sprints, and help design scalable APIs and architectures under senior engineering guidance.