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Vetted Anomaly Detection Professionals
Pre-screened and vetted.
Staff-level Software Engineer specializing in LLM inference infrastructure and scalable model serving
Senior AI/ML Engineer specializing in NLP, LLMs, and retrieval systems
Executive Technology & Product Leader specializing in AI, Cloud, and Cybersecurity platforms
Staff Machine Learning Engineer specializing in LLMs and Generative AI
Principal/Senior Architect specializing in AI platforms and cybersecurity
Senior Full-Stack Software Engineer specializing in cloud storage and developer tooling
Principal Data Scientist & AI/ML Engineer specializing in LLMs, recommender systems, and MLOps
Senior AI Engineer specializing in LLMs, RAG, and production ML systems
Senior Full-Stack Software Engineer specializing in AI platforms and cloud data systems
Staff Full-Stack Software Engineer specializing in cloud platforms and real-time health data
Staff Data Scientist specializing in machine learning, deep learning, and big data
Executive AI/ML Engineer specializing in LLMs, NLP, and production ML systems
Staff Machine Learning Engineer specializing in search, ranking, and LLM systems
Senior AI/ML Engineer specializing in LLMs, recommendation systems, and ML platforms
Senior Software Engineer specializing in full-stack systems and ML-driven platforms
Staff AI/ML Engineer specializing in LLMs, fraud detection, and MLOps
Senior Data Engineer specializing in cloud data platforms and real-time streaming
Senior Full-Stack Engineer specializing in AI and GenAI platforms
Upender Mula
Mid-level Software Engineer specializing in backend systems, real-time data pipelines, and FinTech
“Backend/platform engineer who has owned real-time reporting and streaming analytics systems end-to-end, combining FastAPI/Postgres APIs with Kafka consumers, Celery background jobs, and Redis caching. Strong DevOps/GitOps experience deploying Python/Node microservices to AWS EKS with Helm, ArgoCD/FluxCD, and CI pipelines, and has supported phased on-prem to AWS migrations using Terraform and traffic cutovers.”
Kaye Kirschner
Director-level product leader specializing in AI, data, and FinTech products
“Product leader at Mastercard who has repeatedly built and commercialized AI-driven fraud products across payments and healthcare, including a patented ML approach and a fraud suite that won 30+ enterprise customers in its first year. Stands out for combining deep ML product judgment with workflow design, explainability, and human-in-the-loop thinking to drive real operational change.”
Yusuke Doi
Senior Full-Stack Engineer specializing in AI automation and observability
“Full-stack engineer with recent startup experience building AI automation products end to end, from React/Next.js interfaces to Python/FastAPI services and Dockerized deployment. Particularly strong in reliability, observability, and workflow tooling for non-technical business users, with additional experience optimizing database-backed monitoring systems at Meta.”
Pradeep Nadella
Mid-level AI/ML Engineer specializing in LLM optimization and real-time fraud/risk modeling
“ML engineer with 5 years at Stripe building and productionizing real-time fraud detection at massive scale (3M+ transactions/day; $5B+ annual payment volume). Delivered measurable impact (22% accuracy lift, 18% loss reduction, +3–5% authorization rates) and has strong MLOps/orchestration experience (Docker, Kubernetes, Airflow, MLflow, CI/CD, monitoring/rollback) plus a structured approach to LLM agent/RAG evaluation.”