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

Design, implement, and maintain production-oriented NLP and LLM models; build data pipelines and HPC analyses; integrate ML solutions with clinical research tools; ensure data quality, privacy compliance, and collaborate across multidisciplinary teams.

Design conversational flows for AI-driven chat and voice assistants, collaborating with machine learning, engineering, product, and UX teams. Use NLU and LLM expertise to refine models, develop prompts, shape conversational AI strategy, and create inclusive, accessible experiences. Present design rationale through storytelling and documentation, analyze user and market data, and iteratively improve products using feedback and insights.

Design, build, and deploy scalable AI and ML solutions by wrangling and integrating data, implementing models (Python/Java, TensorFlow, Scikit-Learn), developing data pipelines and NLP applications, collaborating with clients, and mentoring junior team members to drive business insights and regulatory risk solutions.

Lead a team to deliver AI powered products, leveraging machine learning and NLP for customer applications, while collaborating with cross-functional teams.

Lead design and delivery of enterprise semantic-data solutions and knowledge graphs, integrating structured and unstructured data for AI/ML and analytics. Build semantic pipelines, graph-backed services, and integrations (Python/Java), support NLP/embedding use cases, evaluate platforms, define governance/quality controls, run workshops, mentor teams, and drive prototypes through production for regulated clients.

Build, tune, and QA conversational AI agents on the Regal platform: design prompts and flows, tune STT/LLM/TTS settings, create custom functions, test agents, codify best practices, and provide product feedback and sales demos.

Design and ship production LLM features for a SaaS product: build customer intelligence from recordings and text, prioritize testimonials using metadata, create AI-powered surveys/interviews, iterate via research, prototyping, deployment, and evaluation. Own technical decisions and deliver measurable outcomes working closely with engineering leadership and customers.

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

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.

Lead end-to-end performance of customer-facing conversational AI and knowledge base. Design, test, and optimize AI conversations, define intents and success metrics, analyze KPIs, maintain enterprise knowledge, run continuous improvement using analytics and experimentation, and partner cross-functionally to improve CX and business outcomes.