Vetted Apache Spark Professionals

“Unity/VR developer working on real-time Formula 1 broadcast simulations, including a 3D VR experience that lets users follow any car and compare qualifying laps using live F1 data. Built a proprietary math engine and JSON-based pipeline to drive accurate real-time car positioning in Unity; the 7-month effort became the team’s MVP and significantly increased app engagement.”

“Built and deployed a production LLM-powered university support chatbot on Azure using a RAG pipeline, focusing on reducing hallucinations, improving latency, and handling ambiguous queries via confidence checks and clarification prompts. Also has hands-on orchestration experience (Airflow/Azure Data Factory), including hardening a demand-forecasting ingestion workflow with sensors, retries, and automated alerts, and uses a metrics-driven testing/monitoring approach for reliable AI agents.”

“Chief of Staff and public-sector leader who has stood up new functions from scratch—hiring 26 people and building governance/processes across 8 locations—while navigating high-stakes regulatory stakeholders. In industry, implemented OKRs and performance systems (Leapsome) and led change communications to improve executive productivity and cross-team accountability.”

“AI/ML engineer who led Impacter AI’s production deployment of a specialized outreach LLM (CharmedLLM) fine-tuned on GPT-4.1, cutting API costs ~40% while boosting outreach effectiveness ~60%. Built the supporting MLOps and data infrastructure (MLflow, Kubernetes, PySpark, Kafka) and has agentic AI experience from University of Dayton, using LangChain + RAG and vector search (Pinecone) to improve reliability and reduce hallucinations.”

“GenAI/LLM engineer with production experience at Allstate building an end-to-end document intelligence workflow for insurance operations—automating document intake, classification, and risk signal extraction. Emphasizes high-reliability design for regulated/high-stakes outputs using schema enforcement, confidence thresholds, validation rules, and human-in-the-loop routing, with metric-driven offline evaluation and production monitoring.”