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Sidh Humza

@sidhhumza

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Senior AI/ML engineer building production LLM and agentic AI systems with RAG, fine-tuning, and MLOps excellence.

United States

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What I'm looking for

I’m looking to lead end-to-end LLM/agentic AI builds—RAG, fine-tuning, evaluation, and compliant MLOps—while partnering with product and compliance to ship measurable, responsible AI at scale.

I’m a Senior AI/ML Engineer with 9+ years architecting production LLM and agentic AI systems across healthcare, fintech, and cloud domains. I specialize in RAG with hybrid search, fine-tuning (LoRA/QLoRA), and agent orchestration (LangGraph, CrewAI), and I’ve deployed HIPAA-compliant solutions at enterprise scale.

Most recently at Zencore, I designed RAG pipelines using LangChain, LlamaIndex, Pinecone, and hybrid retrieval (BM25 + dense), cutting retrieval latency by 40%, and built agentic workflows for automated customer support and document processing. I also led LLM evaluation (DeepEval, Ragas) to reduce hallucinations by 35%, optimized inference cost with vLLM and quantization (GGUF/AWQ/GPTQ) saving 30% on API expenses, and implemented governance and audit trails to meet HIPAA/GDPR requirements.

Experience

Work history, roles, and key accomplishments

Current

Senior AI/ML Engineer

Current

Zencore

Apr 2023 - Present (3 years 1 month)

Designed and deployed production RAG systems using LangChain/LlamaIndex with hybrid BM25+dense retrieval, cutting retrieval latency by 40%. Built agentic workflows with LangGraph/CrewAI and fine-tuned Llama 3 and Mistral with LoRA/QLoRA for 25% accuracy gains, reducing hallucination rates by 35% while managing model lifecycle on AWS Bedrock/SageMaker with MLflow and Evidently AI under HIPAA/GDPR.

Lang Chain LlamaIndex Pinecone LangGraph Crew AI LoRAs QLoRA MLFlow VLLM

Machine Learning Engineer

AlediumHR

Feb 2019 - Mar 2023 (4 years 1 month)

Built patient readmission risk models using LSTM/GRU and XGBoost, reducing hospital readmissions by 18%. Deployed Clinical BERT/BioBERT entity extraction (92% F1), created HIPAA-compliant EHR ETL with Apache Spark and Azure Data Factory, and implemented real-time patient alerting with Kafka/PySpark and Isolation Forest while establishing MLflow/Azure ML MLOps with SHAP explainability for regulator

XGBoost Apache Spark Azure Data Factory Kafka MLFlow SHAP

Associate Data Scientist

Markovate

Jan 2017 - Jan 2019 (2 years)

Developed a fraud-detection ensemble with XGBoost, LightGBM, and Isolation Forest, reducing false positives by 35%. Built credit scoring with Logistic Regression and Gradient Boosting to improve approval accuracy by 22%, implemented real-time fraud prevention processing 50K+ transactions/minute with Kafka/Redis and scikit-learn, and created customer segmentation using K-Means/DBSCAN with MLflow-ma