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Vetted AI & Machine Learning Professionals in New York
Pre-screened and vetted in New York.
Mid-level AI/ML & Generative AI Engineer specializing in LLMs and MLOps
Intern AI/Data Engineer specializing in NLP, RAG systems, and cloud-native data platforms
Intern AI Software Engineer specializing in RAG and distributed systems
Mid-level Generative AI Developer specializing in secure RAG and data engineering
Mid-level Machine Learning & AI Engineer specializing in GenAI agents and scalable ML pipelines
Mid-level AI/ML Engineer specializing in banking risk, fraud detection, and NLP
Mid-level Applied AI Scientist specializing in multimodal LLM and document intelligence systems
Mid-level Machine Learning & Full-Stack Engineer specializing in LLM platforms and cloud-native apps
Mid-level AI/Data Engineer specializing in LLM agents, RAG, and cloud data pipelines
Intern AI/ML Engineer specializing in LLM agents and healthcare data science
Mid-level Applied AI/ML Engineer specializing in scalable generative model infrastructure
Staff GenAI Solutions Architect specializing in LLMs, RAG, and AI platforms
Adithya Gururaj
Junior AI Engineer specializing in agentic AI, RAG, and voice/telephony systems
“LLM/agent engineer who has built production multi-agent systems (LangChain/LangGraph) for enterprise workflows like email and calendar automation, with a strong focus on latency, tool-calling accuracy, and evaluation via LangSmith. Also worked on AI long-term memory using knowledge graphs at VEAI and communicated the approach and tradeoffs to CEO/CTO stakeholders.”
Mid-level Machine Learning Engineer specializing in LLMs, Generative AI, and MLOps
Tanweer Ashif
Mid-level AI/ML Engineer and Data Scientist specializing in LLMs and MLOps
“Data science/AI intern at University at Buffalo Business Services who built and deployed production systems spanning classic ML and LLM assistants. Delivered real-time competitor intelligence for a Cornell-partnered, $1B beverage launch by scraping/cleaning 5,000+ SKUs and deploying models via API, then built a domain-aware LLM assistant to modernize Excel-based workflows with strong grounding, privacy controls, and sub-5s latency.”