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Vetted AI & Machine Learning Professionals in New York
Pre-screened and vetted in New York.
Popular Titles
Prakhar Dungarwal
Senior Data Scientist specializing in Generative AI and LLM evaluation
Zheng Zhang
Senior Applied Scientist specializing in LLMs, GenAI systems, and AutoML
Niteesh Singh
Mid-level AI/ML Engineer specializing in LLM training, RAG, and low-latency inference
Kenil Tanna
Staff-level Machine Learning Engineer specializing in LLMs and MLOps for Financial Services
“Machine learning/NLP practitioner at J.P. Morgan who led development of a production RAG system and an entity resolution pipeline for complex financial data. Deep hands-on experience with embeddings (Sentence-BERT), vector search (FAISS/pgvector), LLM fine-tuning (LoRA/PEFT), and rigorous evaluation (human-in-the-loop + A/B testing) backed by strong MLOps on AWS (Docker/Kubernetes, MLflow, Prometheus/Datadog).”
Krishna Reddy
Mid-level AI/ML Engineer specializing in fraud detection and clinical LLM assistants
“Built and deployed a production clinical support LLM assistant at Mayo Clinic using a LangChain-orchestrated RAG architecture (Llama 2/PaLM) over de-identified clinical records, integrating BigQuery with Pinecone for semantic retrieval. Focused on healthcare-critical reliability by reducing hallucinations through grounding, implementing HIPAA-aligned privacy controls (Cloud DLP, VPC Service Controls), and running structured evaluations with clinician feedback.”
Ashi Sinha
Junior Software Engineer specializing in full-stack and ML/NLP systems
“Entry-level full-stack engineer with internship experience at Amazon (Appstore IAP flow + uninstall recommendation workflow) and a health-tech startup (OneVector) where they built a DSUR reporting workflow end-to-end, including document generation, S3-backed versioning/metadata, and secure preview/download. Demonstrates strong production debugging and reliability mindset (instrumentation, deterministic retrieval, idempotent writes) and focuses on UX/performance in high-stakes user flows.”
Chenghui Cai
Director of Applied Sciences specializing in reinforcement learning and agentic AI for finance
“Embodied AI/robotics ML engineer with hands-on experience deploying POMDP-based reinforcement learning controllers on real mobile robots and vehicle fleets. Strong in sim-to-real robustness (domain randomization) and production rollout practices (HIL, shadow-mode, canaries, safety instrumentation), and has published related work (mentions a NeurIPS paper).”
Indu Reddy
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and real-time recommendation systems
Devdatt Golwala
Mid-level Data Scientist/ML Engineer specializing in LLMs, NLP, and recommender systems
Abhinav Bachu
Mid-level AI/ML Engineer specializing in cloud MLOps and GenAI for fraud detection
Aryamaan Saha
Intern AI/ML Engineer specializing in LLM systems and cloud-native microservices
Waasi Jagirdar
Junior AI/ML Engineer specializing in LLMs, RAG, and document intelligence
Sarthak Gupta
Mid-level AI/ML Engineer specializing in LLMs, NLP, and real-time AI systems
“Backend engineer who built a real-time pipeline for recording, transcribing, and analyzing audio from 400+ news radio stations, scaling Whisper on an HPC cluster with 7 H100 GPUs. Has strong performance optimization experience (30% latency reduction via SQL/query design; 50% DB call reduction via Redis caching) and has implemented region-based data isolation and PII protections in a regulated environment (JP Morgan Chase).”
Praveen Nutulapati
Mid-level Generative AI Engineer specializing in LLM fine-tuning, RAG, and agentic systems
“Built and deployed a production multi-agent RAG system at JPMorgan Chase to automate regulated credit analysis and compliance clause discovery across large internal policy/document libraries. Implemented LangGraph-based supervisor orchestration with structured state management (Azure OpenAI) to support long-running, resumable workflows, plus hybrid retrieval + re-ranking and guardrails for reliability. Strong at evaluation/observability (trace logging, LLM-judge, HITL) and at communicating results to non-technical stakeholders via Power BI embeds and Streamlit prototypes.”
Srilekha Jajala
Senior AI/ML Engineer specializing in Financial Services and Security
Randy Hollins
Senior Data & AI/ML Engineer specializing in LLM/NLP platforms and cloud data engineering
Tanmay Sharma
Intern AI/ML Engineer specializing in LLM agents, RAG, and applied ML
Vivek Kothapalli
Mid-level AI/ML Engineer specializing in quantitative finance and LLM-based NLP
Harun Bansode
Mid-level Machine Learning Engineer specializing in NLP, recommender systems, and MLOps
Harshitha Kesani
Mid-level Machine Learning Engineer specializing in MLOps, NLP, and quantitative trading