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

Design and deliver LLM-powered, agentic AI systems to automate customer support and compliance. Build scalable, secure backend infrastructure in Python and Go, integrate third-party models/APIs, implement grounding and guardrails, and measure performance. Lead end-to-end projects, mentor engineers, conduct code reviews, and participate in on-call and incident response to improve resolution times and reduce operational costs.

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.

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.

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.

Train large-scale deep learning models for AI-generated content detection, create synthetic datasets, conduct research in adversarial robustness and interpretability, and develop innovative model improvements. Publish research through technical papers and posts, ship production code, deploy models, build infrastructure, and collaborate with engineering and product teams to turn research into product features.

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.

Design, develop, and deploy ML, NLP, and generative-AI solutions (including LLMs and RAG) to improve search, retrieval, recommendation, and question-answering across scientific publications and datasets. Build scalable pipelines, evaluation frameworks, and production-quality Python code while collaborating with engineering, product, UX, and domain experts to measure and improve model reliability, relevance, and user impact.

Annotate and manage training/test datasets, run model training, evaluate model performance, perform manual QA and error analysis, and refine annotation guidelines for NLP/ML projects.

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.

The Senior AI Engineer will develop core AI systems for healthcare, focusing on real-time inference and NLP pipelines, ensuring safety and scalability in medical consultations.