Vetted BigQuery Professionals

“LLM/MLOps engineer who has shipped production systems for complaint intelligence and contact-center NLU, including LoRA/RLHF-tuned LLaMA models deployed on GKE with vLLM and Vertex AI batch pipelines to BigQuery. Demonstrates strong practical focus on hallucination control, data imbalance mitigation, and production monitoring (Langfuse) with regression testing and canary rollouts, plus experience orchestrating complex workflows with AWS Step Functions.”

“Full-stack developer who built a learning management web app end-to-end using React, Spring Boot, and MySQL, integrating APIs via Axios and validating/testing with Postman. Has experience handling data-heavy workloads (courses, quiz results) and improving performance with pagination, and is comfortable designing microservice-style endpoints with CI/CD considerations.”

“AI/ML engineer (Cognizant) who built a production, real-time credit card fraud detection platform combining deep-learning anomaly detection with an LLM-based explanation layer. Strong focus on regulated deployment: addressed class imbalance and feature drift, and added guardrails (SHAP/structured inputs, fine-tuning on analyst reports, rule-based validation) to keep explanations accurate and compliant. Orchestrated the full pipeline with Airflow + Databricks/Spark and used MLflow/Prometheus plus A/B and shadow deployments for measurable reliability.”

“Data/ML engineer with experience across pharma (Dr. Reddy Laboratories) and financial services (Cincinnati Financial, Capital One), building production NLP and entity-resolution systems that connect messy unstructured text with enterprise SQL data. Delivered semantic search with BERT + vector DB and domain fine-tuning (reported ~35% relevance lift), and builds robust pipelines using Airflow/dbt/Spark with strong validation, monitoring, and stakeholder-aligned rollout practices.”

“Engineering leader (player-coach) recently at Autodesk driving a major sales-motion transformation spanning account hierarchy, commissions/quotas, and downstream financial/sales forecasting impacts. Led cross-functional design with enterprise architects and shipped the end-to-end release, using POCs and Anaplan what-if modeling to validate a risky hierarchy change while coordinating delivery across India/Singapore teams and instituting structured Jira-based tech debt/support tracking and automation (dbt, GitHub Copilot).”