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Vetted ELT (Extract, Load, Transform) Professionals
Pre-screened and vetted.
Mid-level Data Engineer specializing in cloud data platforms and streaming pipelines
Mid-level Data Engineer specializing in cloud-native big data pipelines and analytics
Chandra sai kiran Kammari
Mid-level Machine Learning Engineer specializing in fraud detection and real-time personalization
“ML/LLM engineer with Stripe and Adobe experience who productionized a transformer-based Payments Foundation Model for real-time fraud detection at global scale (billions of transactions). Built petabyte-scale ETL/feature pipelines (Spark/EMR, Airflow, dbt, Kafka/Flink) and achieved <100ms multi-region inference (EKS, TorchServe, edge/Lambda, GPU/CPU routing) with strong PCI-DSS/GDPR compliance and explainability (SHAP/LIME), reporting a 64% fraud accuracy improvement.”
ALEXANDER SHEYNER
Executive IT & Enterprise Architecture leader specializing in portfolio transformation, data/AI, and M&A
“Fractional CTO supporting early-stage teams in the UAE and Ukraine to build platforms using an "Agentic OS" approach—one focused on reducing friction across patient/provider/payor engagement and another on enforcing transparency for international rebuilding investments to reduce fraud. Also exploring an alternative-energy feedstock plantation opportunity in Armenia with multi-industry downstream revenue potential; has created project-specific investor pitch decks and is actively engaging potential investors.”
Senior Software Engineer specializing in AI platforms for healthcare and industrial time-series ML
Staff Machine Learning Engineer specializing in LLMs, recommendations, and MLOps
Principal AI Architect specializing in GenAI, agentic systems, and RAG
Director of Enterprise Analytics specializing in AI/ML for healthcare and insurance
Mid-level Machine Learning Engineer specializing in fraud detection and recommendations
Asrith Velireddy
Mid-level AI/ML Engineer specializing in MLOps, LLMs, and scalable ML systems
“ML/LLM engineer at Adobe who deployed a transformer-based personalization and campaign-targeting recommender system end-to-end, including PySpark/Airflow pipelines processing 12M+ events/day and containerized inference on AWS SageMaker (Docker/Kubernetes). Also has hands-on LLM workflow experience (RAG, semantic search, prompt optimization, hallucination mitigation) with a metrics-driven approach to reliability, drift monitoring, and reproducible retraining via MLflow.”
Mid-level Python Developer specializing in cloud data engineering and ETL/real-time pipelines
Mid-level Data Engineer specializing in analytics, BI dashboards, and ETL pipelines
Mid-level Python Full-Stack Developer specializing in FinTech and real-time data/ML systems
Executive Technology Leader (CTO/CIO) specializing in cloud, AI, and enterprise transformation
Senior AI/ML Software Engineer specializing in LLM and RAG systems
Mid-level Machine Learning Engineer specializing in recommender systems and LLM/RAG pipelines
Senior Solutions Architect specializing in cloud infrastructure, AI/LLM security, and data platforms
Technology Executive specializing in AI-native engineering and cybersecurity governance
Mid-level AI/ML Data Engineer specializing in data pipelines, MLOps, and LLM/RAG systems