Mid-level AI/ML Engineer specializing in NLP, MLOps, and scalable data pipelines
Remote, USAAI/ML Engineer5 years experienceMid-LevelFinancial ServicesHealthcareHealthcare IT
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About
Built and shipped a production LLM-powered personalized client engagement assistant in the financial domain, balancing real-time recommendations with strict privacy/compliance requirements. Demonstrates strong MLOps/LLMOps depth (Airflow + MLflow, containerized microservices, drift monitoring) and a privacy-by-design approach validated in collaboration with risk and compliance teams.
Experience
AI/ML EngineerJPMorgan Chase (JPMC)
AI/ML EngineerThe Cigna Group
Education
University of Daytonmaster, Computer Science (2025)
Vignan Institute of Information Technologybachelor, Electrical and Electronics Engineering (2021)
Key Strengths
Built and deployed an LLM-powered real-time financial content recommendation/engagement assistant to production
Privacy-by-design implementation for sensitive financial data (masking/tokenization/encryption, least-privilege access, auditable pipelines)
Efficient model adaptation using LoRA without full retraining
Production-grade MLOps: containerized microservices, continuous monitoring, and drift detection
Orchestrated end-to-end ML workflows with Apache Airflow (ingestion through retraining) with robust failure/retry handling
Integrated Airflow with MLflow for experiment tracking, artifact/metric logging, and auditability
Structured evaluation approach: modular agent/workflow design, unit/integration tests, offline metrics + A/B testing and feedback loops in production
Strong cross-functional collaboration with product, risk, and compliance stakeholders; translates regulatory constraints into technical requirements
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