Mid-level AI/ML Engineer specializing in MLOps and LLM applications
New York, NYAI/ML Engineer4 years experienceMid-LevelFinancial ServicesTechnologyIT Services & Consulting
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About
BNY Mellon engineer who has built and operated production AI systems end-to-end: a LangChain/Pinecone RAG platform scaled via FastAPI + Kubernetes to 1000 RPM with 99.9% uptime, supported by monitoring and data-drift detection. Also deep in data/infra orchestration (Airflow, Dagster, Terraform on AWS/EMR/EC2), processing 500GB+ daily and delivering measurable reliability and performance gains, plus strong compliance-facing model explainability using SHAP and Tableau.
Experience
AI/ML EngineerBNY Mellon
Data ScientistTavant Technologies
Machine Learning InternVerzeo
Education
State University of New York at Albanymaster, Data Science
VNR Vignana Jyothi Institute of Engineering and Technologybachelor, Electrical and Electronics Engineering
Key Strengths
Architected and deployed production RAG system (LangChain + Pinecone) for real-time document querying
Scaled FastAPI service to 1000 requests/min with Kubernetes horizontal autoscaling while maintaining 99.9% uptime
Implemented automated monitoring, data drift detection, and self-healing workflows to prevent user impact
Operated high-volume systems: 10,000+ daily queries and 500GB+ daily data processing
Built orchestration pipelines with Airflow and Dagster; reduced pipeline processing time by 30%
Improved pipeline reliability by 40% via Terraform + Dagster sensors (retries, cleanup, drift detection)
Designed measurable AI workflow evaluation using A/B testing and real-time metric monitoring
Strong stakeholder communication: explained credit risk model drivers with SHAP and delivered exec-ready Tableau dashboards
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