Available to hire
I am Sashank Punyamurthy, an AI/ML Engineer with 4+ years of experience architecting high-scale predictive platforms across Healthcare and Finance. I specialize in the full ML lifecycle, from distributed data engineering with Spark, Kafka and Databricks to deploying production-grade models via Kubeflow, MLflow and Kubernetes.
I work on Clinical NLP (BioBERT, ClinicalBERT), Medical Imaging (MONAI), and real-time Financial Fraud Detection (XGBoost, BERT). I build HIPAA-compliant pipelines, SMART on FHIR integrations, and Responsible AI frameworks to deliver interpretable, regulatory-grade deployments in complex enterprise environments.
Skills
Language
English
Fluent
Work Experience
AI/ML Engineer at Cigna
March 1, 2024 - PresentAI/ML Engineer building a Generative AI-powered healthcare/insurance assistant using Retrieval-Augmented Generation (RAG) and large language models. Implemented end-to-end document ingestion (PDF parsing, cleaning, chunking, embeddings), FAISS-based vector similarity search, and LangChain tool-based workflows. Developed a secure FastAPI inference service, containerized with Docker, and deployed on Kubernetes (basic) and AWS (S3, EC2/SageMaker). Applied prompt engineering and guardrails for policy-compliant responses with citation-style outputs and metadata-based filtering to improve recall. Tracked experiments with MLflow for reproducibility and managed model iterations.
Machine Learning Engineer at J.P. Morgan
February 1, 2022 - July 1, 2023Developed an end-to-end real-time fraud detection and credit risk scoring system. Performed feature engineering on transaction velocity, device/IP risk signals, and user behavior; addressed class imbalance with SMOTE and weighted losses while tuning thresholds. Built models using XGBoost and Scikit-Learn, achieving strong ROC-AUC, F1, and precision/recall metrics. Designed batch and near real-time scoring pipelines with Pandas/SQL, and a FastAPI inference service. Implemented MLflow for experiment tracking and model versioning, and automated training/deployment with Apache Airflow. Created dashboards (Tableau/Power BI) to monitor fraud trends, drift, and risk metrics. Containerized components with Docker for consistent deployments.
ML Engineer / Data Scientist at JP Morgan
February 1, 2022 - July 1, 2023Developed an end-to-end Fraud Detection and Credit Risk Scoring system for fintech transaction datasets using supervised learning. Performed feature engineering on transaction velocity, device/IP risk signals, and user behavior. Addressed class imbalance with SMOTE and tuned models (XGBoost, Scikit-Learn) achieving strong ROC-AUC, F1, and precision/recall. Built batch/near real-time scoring pipelines with Pandas/SQL and deployed a FastAPI inference service. Managed model lifecycle with MLflow and automated training with Apache Airflow. Created dashboards with Tableau/Power BI for monitoring fraud trends and model drift. Containerized components with Docker for consistent deployments.
ML Engineer at JP Morgan
February 1, 2022 - July 1, 2023Developed an end-to-end Fraud Detection and Credit Risk Scoring system for fintech transaction datasets. Conducted advanced feature engineering (velocity signals, device/IP risk, user behavior, merchant risk) and addressed class imbalance via SMOTE, weighted losses, and threshold tuning. Built models with XGBoost and Scikit-learn, and designed batch/near real-time scoring pipelines. Implemented a scalable FastAPI inference service, and managed model lifecycle with MLflow. Automated training and deployment workflows using Apache Airflow. Created analytics dashboards in Tableau/Power BI to monitor fraud trends, drift, and risk metrics. Containerized components with Docker for consistent deployments.
AI/ML Engineer at Cigna Healthcare
March 1, 2024 - PresentDesigned and deployed a machine learning-driven clinical risk prediction platform analyzing longitudinal EHR, claims and clinical notes via FHIR APIs and HL7 pipelines, enabling early identification of high-risk patients across chronic disease cohorts. Built scalable feature engineering and data ingestion pipelines with Apache Spark, Kafka and Databricks, processing patient records and clinical events, improving predictive model training throughput by 55%. Developed NLP pipelines for clinical text analysis using Spark NLP, BioBERT and ClinicalBERT to extract comorbidities, medication patterns and adverse events from physician notes, improving risk stratification model accuracy by 18%. Implemented medical imaging AI workflows using MONAI and PyTorch to support radiology-assisted diagnostics through automated anomaly detection across DICOM imaging streams from PACS systems, reducing manual review workload for radiology teams. Integrated predictive models into clinical applications throug
AI/ML Engineer at JP Morgan Chase, Hyderabad
February 1, 2021 - July 1, 2023Architected distributed data processing pipelines using PySpark and Dask on AWS to ingest and pre-process millions of daily global transactions from Oracle and Snowflake, ensuring high-throughput data availability for real-time risk assessment. Developed and deployed hybrid predictive models combining XGBoost for tabular behavioral analysis and BERT-based Financial NLP to analyze unstructured transaction memos, specifically designed to detect layering patterns in sophisticated financial crimes. Established an end-to-end ML lifecycle using Kubeflow Pipelines and MLflow, integrating automated Model Monitoring and Drift Detection to ensure scoring accuracy remained consistent despite shifting market volatility and evolving regulatory requirements. Containerized and orchestrated model microservices using Docker and Kubernetes (EKS), streamlining the deployment of REST APIs through Jenkins CI/CD to provide low-latency fraud scores to downstream banking applications. Reduced false-positive a
Education
Master of Science in Information Technology at University of Cincinnati
August 1, 2023 - December 1, 2024Bachelor of Technology in Information Technology at Vellore Institute of Technology (VIT)
August 1, 2019 - August 1, 2023Master of Science (MS), Information Technology at University of Cincinnati
August 1, 2023 - December 1, 2024Bachelor of Technology (B.Tech), Information Technology at Vellore Institute of Technology (VIT)
August 1, 2019 - August 1, 2023Master of Science (MS), Information Technology at University of Cincinnati
August 1, 2023 - December 1, 2024Bachelor of Technology (B.Tech), Information Technology at Vellore Institute of Technology (VIT)
August 1, 2019 - August 1, 2023Master of Science (MS), Information Technology at University of Cincinnati
August 1, 2023 - December 1, 2024Bachelor of Technology (B.Tech), Information Technology at Vellore Institute of Technology (VIT)
August 1, 2019 - August 1, 2023Master of Science (MS) in Information Technology at University of Cincinnati
January 11, 2030 - April 17, 2026Bachelor of Technology (B.Tech) in Information Technology at Vellore Institute of Technology (VIT)
January 11, 2030 - April 17, 2026Qualifications
Industry Experience
Healthcare, Financial Services, Software & Internet, Professional Services, Education
Skills
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