Top Natural Language Processing (NLP) Jobs in NYC, NY

As an Applied Research Engineer, you will enhance NLP systems and build LLM-enabled products, running experiments and integrating advanced techniques into software systems.

Evaluate and improve AI Coach chat outputs for financial planning, identify risks and inaccuracies, escalate issues, contribute reusable solution libraries, define intent keywords, and suggest product and chatbot enhancements to improve member experience and compliance.

The AI Conversation Designer will create and maintain AI customer support experiences, focusing on chatbot dialogue, QA processes, and integrations, using analytics and best practices.

The role involves collaborating with teams to develop AI-powered products, leveraging NLP and LLM technologies while operationalizing models into production systems.

Design and run advanced analyses and machine learning/NLP models on large multimodal mental-health datasets. Build preprocessing, feature engineering, validation, and visualization pipelines; write scalable documented code for HPC environments; use version control and containerization; collaborate on project planning and present scientific findings while responsibly handling sensitive data.

The Head of Technology oversees the architecture and operations of a behavioral intelligence platform, leading a high-performance team and managing strategic integrations. Responsibilities include building cloud-native infrastructure, designing natural language interfaces, and ensuring data privacy and governance.

Lead development and implementation of conversational and agentic AI solutions for contact centers. Manage cross-functional teams, translate client requirements into technical specs, design responsive UIs using AngularJS/React/Vue, run usability testing, apply human-centered design, and mentor junior staff while building client relationships to ensure successful delivery of AI-driven products.

As a Data Scientist at Octus, you will design, build, and maintain AI-driven systems, focusing on large language models and productionizing AI solutions while collaborating with cross-functional teams.

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.