Principal ML Engineer at Drive Health

Led design and deployment of a HIPAA-compliant, multi-agent Voice AI for clinical applications; architected and scaled a Hybrid Retrieval-Augmented Generation system using PgVector and HNSW-based indexing with a TinyBERT reranker to reduce hallucinations and boost retrieval precision. Integrated Generative AI Guardrails and custom safety checkers; optimized LLMs with vLLM, FlashAttention, and dynamic batching on AWS EKS, increasing GPU utilization by 30% and cutting average inference latency by 50%. Built distributed fine-tuning pipelines for open-source LLMs (Llama, Gemma) using QLoRA and Instruction Tuning on SageMaker; implemented RLHF with PPO. Implemented MCP server integration with LiveKit and Tavily Search; established Prompt Engineering, HITL feedback loops, and an automated evaluation pipeline with LLM-as-a-Judge.

Founding AI Engineer at Our English LLC

Led end-to-end development and launch of a Voice AI English Tutor within an LMS; established Model Context Protocol layer to enable low-latency bi-directional voice and structured data exchange. Built an event-driven MLOps architecture using AWS SQS and Fargate; developed a Hybrid RAG system with vector search and metadata filtering; trained and deployed multilingual TTS models. Designed an automated LLM-as-a-Judge evaluation framework automating 90% of model QA and reducing rating variance by 20%. Led cross-functional onboarding for Product and Data Science teams and defined core LLM architecture and MLOps standards.

Senior Machine Learning Engineer at Sage Software Inc

Architected Copilot Factory Framework (CFF), an internal LLM orchestration system to rapidly prototype and deploy domain-specific chatbots for financial analysts. Built end-to-end MLOps pipeline using Kubeflow, Terraform, and CloudFormation on AWS EKS; containerized a BERT-based NER model; implemented BERT-based topic modeling (Gensim) for 10M+ records annually; established evaluation and monitoring with Weights & Biases; improved image recognition accuracy to 98% via optimized computer vision pipeline (OpenCV/TensorFlow).

Data Scientist at Databricks

Led large-scale data ingestion and preprocessing for financial markets data using Apache Spark; developed time-series forecasting models (ARIMA, LSTM, GRU), improving predictive accuracy by 18%; built data warehousing solutions in BigQuery with robust ETL; designed a classic Collaborative Filtering recommender engine for internal knowledge discovery, increasing utilization by 25%.