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Vetted Machine Learning Engineers in the NYC Metro
Pre-screened and vetted in the NYC Metro.
Senior AI/ML Engineer specializing in GenAI, LLMs, NLP, and MLOps
Mid-level Machine Learning Engineer specializing in NLP, recommender systems, and MLOps
Mid-level Machine Learning Engineer specializing in LLMs, multimodal AI, and backend systems
silin liu
Mid-level AI/ML Engineer specializing in LLM agents, RAG, and enterprise ML systems
“Built a production multi-agent recommendation/RAG system for internal data analysts to speed up weekly report creation by improving document discovery and automating report/SQL generation. Implemented LangGraph-based orchestration with deterministic agent routing, robust error handling (interrupt/resume), and metadata-driven semantic chunking for diverse PDF/document formats, plus monitoring for latency, throughput, and token/cost efficiency.”
Aarushi Mahajan
Mid-level AI/ML Engineer specializing in NLP, Generative AI, and MLOps
“Internship experience shipping production AI systems: built an end-to-end RAG platform (Python/FastAPI + LangChain/LangGraph + vector search) to answer support questions from unstructured internal docs, with a strong focus on hallucination prevention through confidence gating and rigorous offline/online evaluation. Also delivered an AI-driven personalization/analytics feature using an unsupervised clustering pipeline, iterating with PMs to align statistically strong clusters with actionable business segmentation.”
Balaji Nissenkarao
Mid-level Machine Learning Engineer specializing in AI/LLM systems
“ML/LLM systems engineer who has owned AI support automation products end-to-end, including ServiceNow-integrated incident routing, RAG-based resolution suggestion systems, and production stabilization. Stands out for combining hands-on platform work across PySpark, AWS Glue, FastAPI, Kubernetes, and Pinecone with measurable operational impact, including 30-35% MTTR reduction and 25-30% improvement in first-touch resolution.”
Jaswanth Vakkala
Mid-level Generative AI Engineer specializing in enterprise RAG and multimodal NLP
“Built and deployed a production LLM/RAG chatbot at Wells Fargo for securely querying regulated financial and compliance documents, emphasizing low hallucination rates, explainability, and strict governance. Experienced with LangChain multi-agent orchestration plus Airflow/Prefect pipelines for ingestion, embeddings, evaluation, and retraining, and partnered closely with compliance/operations to drive adoption through demos and feedback-driven retrieval rules.”
Kristina Shen
Intern-level Data Scientist and ML Engineer specializing in analytics and AI systems
“Early-career analytics candidate with hands-on experience in SQL/Python data pipelines, Tableau reporting, and marketing engagement analytics across internship and startup settings. Stands out for combining rigorous data quality practices with practical AI system design, including an end-to-end GPT-4 grading capstone that emphasized explainability and human oversight.”
Mid-level AI/ML Engineer specializing in computer vision, NLP, forecasting, and GenAI
Mid-level Machine Learning Engineer specializing in MLOps, NLP, and financial risk analytics
Mid-level Full-Stack Software Engineer specializing in AI/ML and GenAI platforms
Mid-level Data Scientist specializing in fraud detection and ML pipelines
Mid-level GenAI/ML Engineer specializing in LLM agents and RAG for fraud detection
Senior AI/ML Engineer specializing in FinTech and healthcare analytics
Mid-level AI/ML Developer specializing in healthcare and financial services
Mid-level AI/ML Engineer specializing in credit risk, fraud detection, and NLP in financial services
Mid-level ML Engineer specializing in production NLP, forecasting, and anomaly detection
Senior Machine Learning Engineer specializing in AI, NLP, computer vision, and GenAI
Mid-level AI/ML Engineer specializing in conversational AI, NLP, and LLM-powered RAG systems
Soham Patel
Mid-level Machine Learning Engineer specializing in healthcare NLP and MLOps
“ML/AI practitioner in healthcare (Syneos Health) who has deployed production clinical NLP and risk models. Built a BERT-based physician-note information extraction system on Docker + AWS SageMaker (reported ~42% retrieval improvement) and automated retraining/deployment with Airflow and drift detection, while partnering closely with clinicians to drive adoption (reported ~18% readmission reduction).”
PAVAN VARMA PENMETHSA
Mid-level Machine Learning Engineer specializing in LLM agents, RAG, and MLOps
“Built a production AI-driven contract/document extraction system combining OCR, normalization, and LLM schema-guided extraction, orchestrated with PySpark and Azure Data Factory and loaded into PostgreSQL for analytics. Emphasizes reliability at scale—using strict JSON schemas, confidence scoring, targeted retries, and multi-layer validation to control hallucinations while processing thousands of PDFs per hour—and partners closely with non-technical business teams to refine fields and deliver usable dashboards.”