Vetted Machine Learning Professionals

“AI-focused engineer with Infosys experience building Azure/.NET chatbot applications and recent hands-on work with FastAPI/LangChain. Built a hackathon multi-agent legal counsel system showcasing agent orchestration, and emphasizes production readiness via Docker, GitHub Actions CI/CD, pytest automation, and adversarial simulations for auditable AI behavior. No direct robotics/ROS experience to date.”

“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.”

“Lifecycle/CRM marketer from Churchome who led a mobile app onboarding and re-engagement program using behavior-based segmentation, in-app/push messaging, and AI-assisted chat. Drove ~20% lift in early-stage engagement, improved 30-day retention, and reduced support load through automated chat flows and rapid A/B-driven iteration.”

“Customer success leader (Director of Customer Engagement at PlutoShift; also experience at Truework) focused on enterprise lifecycle ownership, stakeholder mapping, and VoC-driven product influence. Led cross-functional efforts to ship a reporting capability requested by customers, improving adoption and loyalty, and uses tools like Looker/Tableau plus deep customer discovery to diagnose issues like ineffective onboarding even when usage metrics look strong.”

“QA automation engineer who owned an end-to-end, device-integrated mobile regression suite for Tandem’s insulin-pump-connected mobile app, covering pairing/connectivity/data sync and catching contract mismatches and firmware-related connectivity regressions. Strong in Cypress/JavaScript automation, CI gating in GitHub Actions, and diagnosing production-impacting sync issues using logs and API traces while influencing requirements early to improve testability and UX.”

“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.”

“Backend engineer who built and shipped an end-to-end AI outreach product (LazyMails) combining a LinkedIn-scraping Chrome extension with a FastAPI/Postgres backend and Gemini-powered email generation, achieving major personal productivity gains. Also has enterprise experience at TCS on Humana’s 500k+ user wellness platform running Kubernetes microservices with Azure DevOps CI/CD, plus Kafka-based real-time eligibility event streaming and GitOps-driven operations.”