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Vetted AI & Machine Learning Professionals in New York
Pre-screened and vetted in New York.
Popular Titles
shubham patil
Mid-level AI Engineer specializing in Generative AI, RAG systems, and fraud analytics
“Built and deployed a RAG-based student/faculty support chatbot at a university that answers from official syllabus/policy documents and now supports 4,000+ students while reducing repetitive support requests. Hands-on with LangChain, LangGraph, and CrewAI to orchestrate reliable agentic workflows, with a strong focus on testing/monitoring in production and cross-functional delivery (e.g., marketing analytics automation at Steve Madden).”
Gabriel Fagundes
Mid-level AI/ML & Backend Engineer specializing in AI platforms and computer vision
“Backend engineer with hands-on experience building real-time, low-latency systems: owned the Python backend for a real-time crowd-monitoring product (top 5% at HackHarvard 2025) using OpenCV, GPU YOLO inference (PyTorch), WebRTC, and OAuth. Also has production Kubernetes/GitOps experience (Helm/Kustomize, GitHub Actions, Argo CD), Kafka-based event pipelines, and executed a minimal-downtime on-prem PostgreSQL migration to AWS EC2.”
Butchi Venkatesh Adari
Mid-level Machine Learning Engineer specializing in LLM platforms and robotic perception
“Built and shipped a production multi-agent personal financial assistant at AlphevaAI on AWS ECS, combining FastAPI microservices, Redis/SQS orchestration, and Pinecone-based hybrid RAG (semantic + BM25) to ground financial guidance. Improved routing accuracy with an embedding-based SetFit + logistic regression intent classifier feeding an LLM router, and optimized UX with live streaming plus cost controls via model tiering and caching.”
Tadigotla Kumar Reddy
Mid-level AI/ML Engineer specializing in healthcare imaging and GenAI/LLM systems
“Built and deployed a production LLM/RAG clinical document understanding and summarization system for healthcare, focused on reducing manual review time while meeting strict accuracy, latency, and compliance needs. Demonstrates strong MLOps/orchestration depth (Airflow, Kubernetes, Azure ML Pipelines) and a rigorous approach to hallucination mitigation through layered, source-grounded safeguards and stakeholder-driven requirements with physicians/compliance teams.”
Thejas MandyaShashidhara
Intern Full-Stack/AI Software Engineer specializing in web apps and AI workflow automation
Likhitha Uppalapati
Mid-level AI/ML & Generative AI Engineer specializing in LLMs and MLOps
Sukrut Bidwai
Intern AI Software Engineer specializing in RAG and distributed systems
Hemalatha Goli
Mid-level Generative AI Developer specializing in secure RAG and data engineering
Kiran Prakash
Mid-level Machine Learning & AI Engineer specializing in GenAI agents and scalable ML pipelines
Ruchita Ananthaneni
Mid-level AI/ML Engineer specializing in banking risk, fraud detection, and NLP
Sai Naveena Kode
Junior Data Scientist specializing in NLP, RAG, and ML systems
Samar Pratap Singh
Mid-level Machine Learning & Full-Stack Engineer specializing in LLM platforms and cloud-native apps
Anirudha Raghava Sarma Kuchibhotla
Mid-level AI/Data Engineer specializing in LLM agents, RAG, and cloud data pipelines
Viraj Joshi
Intern AI/ML Engineer specializing in LLM agents and healthcare data science
Siddharth Pathania
Mid-level Applied AI/ML Engineer specializing in scalable generative model infrastructure
Anchal Sojatiya
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.”
Badrinath `
Mid-level Machine Learning Engineer specializing in LLMs, Generative AI, and MLOps