Pre-screened and vetted in the NYC Metro.
Senior AI/ML Data Scientist specializing in NLP, computer vision, and MLOps
“Applied LLMs and a graph-RAG architecture in Neo4j to automate an accounting firm's cross-checking of transactional books against tax regulations, indexing 1,000+ pages into a knowledge graph with vector search. Combines agentic LLM workflows with classical NER (Hugging Face/NLTK) and validates using expert-labeled held-out data plus precision/recall and measured accountant time savings after deployment.”
Senior Machine Learning Engineer specializing in Generative AI and NLP
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.”
Mid-level Data Scientist specializing in NLP/LLMs, time series forecasting, and MLOps
“Data/ML practitioner with hands-on experience building NLP systems from prototype to production: delivered a Twitter sentiment classifier with robust preprocessing, SVM modeling, and Power BI reporting, and built entity-resolution pipelines for messy multi-source customer data (reporting ~95% improvement in unique entity identification). Also implemented semantic linking/search using SBERT embeddings with FAISS vector retrieval and domain fine-tuning (reported ~15% precision lift), and applies production workflow best practices (Airflow/Prefect, Docker, Azure ML/Databricks, Great Expectations).”
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 Data Scientist specializing in fraud detection and ML pipelines
Mid-level GenAI/ML Engineer specializing in LLM agents and RAG for fraud detection
Mid-level Data Scientist specializing in experimentation, personalization, and decision intelligence
Mid-level AI/ML Engineer specializing in credit risk, fraud detection, and NLP in financial services
Junior Data Scientist specializing in analytics automation and BI dashboards
Mid-level AI/ML Engineer specializing in Generative AI agents and enterprise analytics
Senior Machine Learning Engineer specializing in AI, NLP, computer vision, and GenAI
Mid-level AI/ML Engineer specializing in NLP, fraud detection, and MLOps
“LLM/ML platform engineer with hands-on experience taking an LLM document summarization prototype into a production-grade service on AWS EKS, emphasizing low-latency inference, drift monitoring, and safe CI/CD rollouts (canary + rollback). Strong in real-time debugging of agentic/RAG systems (tracing, retrieval/index drift fixes) and in developer enablement through practical workshops (Docker/Kubernetes/FastAPI) plus pre-sales support via demos and benchmarks to close pilots.”
Mid-level Machine Learning & GenAI Engineer specializing in LLMs, RAG, and NLP
“Built and deployed an LLM-powered customer support assistant (“Notable Assistant”) focused on automating common post-customer queries while maintaining multi-turn context and meeting scalability/latency needs. Experienced with production orchestration and operations using Kubernetes and Apache Airflow (DAG-based ETL, scheduling, monitoring/alerts), and has partnered closely with customer service stakeholders to align chatbot behavior with brand voice through iterative testing.”
Senior AI/ML Engineer specializing in Generative AI, RAG, and LLM fine-tuning
Mid-level Data Scientist specializing in credit risk and fraud analytics
Junior Data Scientist specializing in NLP, fraud detection, and AI/ML systems
Mid-level Data Scientist specializing in AI/ML and Generative AI
Mid-level Data Scientist/Data Engineer specializing in ML, MLOps, and real-time data pipelines
Mid-level Data Scientist specializing in healthcare and financial risk modeling
Mid-level Machine Learning Engineer specializing in safety-critical and uncertainty-aware ML systems
“Built and productionized an LLM-powered assistant for company documents and support questions, focused on reducing time spent searching PDFs/policies/tickets while preventing hallucinations by grounding answers in approved sources. Demonstrates strong production engineering (Kubernetes/orchestration, caching, monitoring, fallbacks) plus security-minded permissioning and close collaboration with operations/support stakeholders.”