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Vetted Apache Spark Professionals
Pre-screened and vetted.
Senior AI/ML Engineer specializing in healthcare and fintech AI systems
Mid-level AI/LLM Engineer specializing in generative AI and ML systems
Mid AI/Machine Learning Engineer specializing in LLMs, NLP, and Computer Vision
Mid-level AI Software Engineer specializing in Generative AI and FinTech
Senior Software Engineer specializing in distributed systems, ML infrastructure, and search
Staff Platform/ML Engineer specializing in agentic AI, RAG, and cloud infrastructure
Senior Full-Stack Python Developer specializing in cloud, data platforms, and GenAI
Mid-level Machine Learning Engineer specializing in fraud detection and recommendations
Mid-level Agentic AI & ML Engineer specializing in LLM agents and RAG systems
Mid-Level Software Engineer specializing in cloud-native backend and distributed systems
Staff AI & Data Engineer specializing in LLM systems and real-time data platforms
Junior Data Scientist & Data Engineer specializing in ML and scalable data pipelines
Mid-level AI/ML Engineer specializing in cloud MLOps and GenAI for fraud detection
Senior Software Engineer specializing in cloud-native systems and Generative AI
Mid-level Data Scientist specializing in FinTech and product analytics
Senior Applied AI Engineer specializing in LLMs, RAG, and computer vision
Mid AI/ML Engineer specializing in LLM alignment and scalable AI systems
Mid-level Full-Stack Software Engineer specializing in cloud-native and data platforms
Executive Engineering Leader (CTO/VP) specializing in platform scaling and video streaming
Ethan Pribble
Senior Software Engineer specializing in cloud cost intelligence and FinOps platforms
“Backend/data engineer with strong authorization and compliance-domain experience: led a phased migration from a simplistic role model to modern RBAC on a Python serverless stack (Auth0 + AWS Lambda/API Gateway), coordinating changes across 5 repos with extensive manual and automated validation. Previously built and operated custom ETL pipelines (Airflow + Groovy/Java on Spark/YARN/Hadoop) to normalize messy customer email/chat/voice data for NLP-driven financial compliance indicators, including complex email journaling metadata enrichment and large-scale remediation reprocessing after production bugs.”