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

Lead multidisciplinary teams to design human-centered, agentic AI experiences—translating complex AI capabilities (LLMs, NLP, generative AI) into intuitive, trustworthy interfaces, rapid prototypes, and deployable tooling while mentoring talent and building client relationships to drive measurable business impact.

As an ML Research Engineer, you'll optimize speech recognition and NLP models, integrate AI components, and develop knowledge graphs. Collaborate with experts, manage rapid experimentation, and publish research.

As a Forward Deployed Engineer, you will fine-tune language models for customer-specific applications, manage training data, debug training processes, and deploy models while collaborating with clients and research teams.

Lead and develop conversational AI models for Decagon's agents, enhancing their capabilities and integrating them into production systems. Collaborate on research to improve AI performance and user satisfaction.

The Tech Lead will design and develop Python-based backend services for NLP and chatbots, support cloud-native technology transformation, and collaborate with stakeholders.

Lead design and implementation of Call Guard's real-time voice AI stack: build production voice agents, optimize sub-second STT→reasoning→TTS latency, defend against adversarial voice attacks, integrate LLMs and speech models, own telephony/VoIP routing and cloud infrastructure, and mentor engineering teams to ship scalable, secure consumer privacy products.

Lead design and validation of agentic AI capabilities for legal workflows using LLMs, NLP, RAG, hybrid search, embeddings and vector databases. Drive experimentation, evaluation, and metrics, translate results to product recommendations, collaborate with engineers and legal experts, and mentor team members.

Develop and productionize NLP and ML solutions (including LLMs and GenAI) to extract insights from unstructured data. Manage research, data preparation, model training/fine-tuning, evaluation, and cross-functional integration into production systems, focusing on sparse data, model explainability, and performance.

Build and own conversational voice AI products end-to-end: architect, implement, and deploy the platform. Design infrastructure, develop front-end and back-end systems, deliver reliable customer outcomes, and collaborate directly with the CTO to scale the product for enterprise customers.

Build, optimize, and maintain the AskCR RAG chatbot across web and mobile. Implement React frontends and Python/FastAPI services, integrate OpenAI LLMs with prompt engineering, deploy via cloud/containerization, collaborate with product and design, and apply responsible AI and security best practices.