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Senior AI/ML Engineer and Data Scientist with 11+ years of experience building production-grade Machine Learning and Generative AI solutions across banking, healthcare, manufacturing, and industrial domains. End-to-end expertise across the ML lifecycle—from data ingestion and feature engineering to evaluation, API deployment, monitoring, retraining, and governed production support. Proven experience delivering enterprise GenAI/LLM platforms (RAG, semantic search, document intelligence, agentic workflows, structured outputs, tool/function calling, and human-in-the-loop review). Strong multi-cloud MLOps/LLMOps background with secure, auditable deployments using Python, SQL, PySpark, FastAPI, Docker/Kubernetes, Terraform, MLflow, and cloud monitoring.…Senior AI/ML Engineer and Data Scientist with 11+ years of experience building production-grade Machine Learning and Generative AI solutions across banking, healthcare, manufacturing, and industrial domains. End-to-end expertise across the ML lifecycle—from data ingestion and feature engineering to evaluation, API deployment, monitoring, retraining, and governed production support. Proven experience delivering enterprise GenAI/LLM platforms (RAG, semantic search, document intelligence, agentic workflows, structured outputs, tool/function calling, and human-in-the-loop review). Strong multi-cloud MLOps/LLMOps background with secure, auditable deployments using Python, SQL, PySpark, FastAPI, Docker/Kubernetes, Terraform, MLflow, and cloud monitoring.

Surya Meka

AI Engineer, Data Scientist, Data Engineer, +3

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Senior AI/ML Engineer and Data Scientist with 11+ years of experience building production-grade Machine Learning and Generative AI solutions across banking, healthcare, manufacturing, and industrial domains. End-to-end expertise across the ML lifecycle—from data ingestion and feature engineering to evaluation, API deployment, monitoring, retraining, and governed production support. Proven experience delivering enterprise GenAI/LLM platforms (RAG, semantic search, document intelligence, agentic workflows, structured outputs, tool/function calling, and human-in-the-loop review). Strong multi-cloud MLOps/LLMOps background with secure, auditable deployments using Python, SQL, PySpark, FastAPI, Docker/Kubernetes, Terraform, MLflow, and cloud monitoring.…Senior AI/ML Engineer and Data Scientist with 11+ years of experience building production-grade Machine Learning and Generative AI solutions across banking, healthcare, manufacturing, and industrial domains. End-to-end expertise across the ML lifecycle—from data ingestion and feature engineering to evaluation, API deployment, monitoring, retraining, and governed production support. Proven experience delivering enterprise GenAI/LLM platforms (RAG, semantic search, document intelligence, agentic workflows, structured outputs, tool/function calling, and human-in-the-loop review). Strong multi-cloud MLOps/LLMOps background with secure, auditable deployments using Python, SQL, PySpark, FastAPI, Docker/Kubernetes, Terraform, MLflow, and cloud monitoring.

Available to hire

Senior AI/ML Engineer and Data Scientist with 11+ years of experience building production-grade Machine Learning and Generative AI solutions across banking, healthcare, manufacturing, and industrial domains. End-to-end expertise across the ML lifecycle—from data ingestion and feature engineering to evaluation, API deployment, monitoring, retraining, and governed production support.

Proven experience delivering enterprise GenAI/LLM platforms (RAG, semantic search, document intelligence, agentic workflows, structured outputs, tool/function calling, and human-in-the-loop review). Strong multi-cloud MLOps/LLMOps background with secure, auditable deployments using Python, SQL, PySpark, FastAPI, Docker/Kubernetes, Terraform, MLflow, and cloud monitoring.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

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Expert

Intermediate

Intermediate

Language

Work Experience

Senior AI/ML Engineer at US Bank

May 1, 2024 - Present

Modernized fraud investigation, compliance review, risk analytics, customer intelligence, and financial document processing using production machine learning, RAG-based retrieval, agentic workflows, and governed multi-cloud deployments. Built enterprise GenAI/ML services with Python and FastAPI, using Azure OpenAI/OpenAI models, Vertex AI, Databricks, BigQuery, LangChain/LangGraph, and MLflow. Developed RAG systems using embeddings, vector stores (Pinecone/FAISS/Chroma/pgvector), metadata filtering, retrieval ranking, structured outputs, and human-in-the-loop review. Implemented agentic workflows with tool/function calling, routing, exception handling, and validation. Designed scalable ingestion and transformation pipelines with BigQuery, Dataflow/Dataproc, Cloud Storage, Databricks/Spark/PySpark, and Azure Data Lake/AWS S3. Built and deployed fraud/anomaly/segmentation/risk models and shipped microservices with Docker, Kubernetes, and multi-cloud security patterns. Added LLM/RAG evalu

Senior AI/ML Engineer at Optum Health

March 1, 2022 - April 30, 2024

Delivered a cloud-native clinical intelligence and generative AI platform for patient risk prediction, clinical NLP, healthcare document understanding, provider assistance, utilization forecasting, population health analytics, and HIPAA-aligned workflows. Built predictive models and NLP solutions using Python, TensorFlow/PyTorch/Scikit-Learn, Vertex AI, BigQuery ML, Databricks, Azure ML, and AWS SageMaker. Implemented distributed data pipelines (SQL, BigQuery, Dataflow/Dataproc, Cloud Storage, Databricks/Spark/PySpark, Azure Synapse/Azure Data Lake, AWS Glue/S3). Developed healthcare NLP with ClinicalBERT/BioBERT and transformers for extraction/classification/summarization. Implemented healthcare RAG using LangChain, Vertex AI Search, BigQuery Vector Search, Pinecone/FAISS/Chroma, secure metadata filters, and embeddings. Applied PHI-aware governance (de-identification, masking, RBAC, audit logging, secure retrieval patterns). Deployed ML/NLP/GenAI services via FastAPI/Flask, Docker, Ku

Machine Learning Engineer at SoFi Bank

January 1, 2020 - February 28, 2022

Built production credit risk analytics and fraud detection models using AWS-first data engineering and scalable inference patterns. Developed ML models in Python/SQL with Scikit-Learn/XGBoost/LightGBM/TensorFlow/PyTorch for fraud detection, underwriting support, credit scoring, customer segmentation, and predictive intelligence. Created feature engineering pipelines using S3, Glue, EMR, Redshift, Spark/PySpark, SQL, and Airflow. Implemented training and deployment workflows with SageMaker Pipelines, ECR, Docker, EKS, Jenkins/GitHub Actions, Terraform, and MLflow model registry. Delivered batch and real-time inference services via FastAPI/Flask APIs and AWS Lambda/EKS with secure integration patterns. Added champion-challenger testing, retraining, drift checks, monitoring dashboards/alerts (CloudWatch/Prometheus/Grafana), and governance via SHAP/LIME and validation documentation.

Machine Learning Engineer at Caterpillar

October 1, 2017 - December 31, 2019

Developed predictive maintenance and smart manufacturing analytics to reduce downtime and improve equipment reliability. Built predictive maintenance/equipment reliability and anomaly/time-series models using Python, SQL, Scikit-Learn, XGBoost, Random Forest, and gradient boosting, including rolling-window/lag feature engineering. Processed telemetry and maintenance/service/inventory data using S3, EMR, Spark/PySpark, Pandas/NumPy, and SQL. Created forecasting and optimization models for demand/inventory/spare parts and supplier performance. Produced Tableau/QuickSight dashboards for downtime, failures, maintenance schedules, utilization, OEE-style metrics, and operational KPIs. Conducted root-cause analysis, validation, and data quality checks and supported production analytics modernization in an Agile environment.

Data Scientist at Cummins

July 1, 2015 - September 30, 2017

Delivered customer intelligence and demand forecasting analytics for forecast accuracy, retention, revenue planning, and operational reporting. Partnered with sales/finance/ops/product/BI teams to translate KPIs and business questions into statistical learning solutions. Built demand forecasting, churn prediction, segmentation, and pricing analytics using Python/SQL and Scikit-Learn with regression trees/random forests/gradient boosting and time-series methods. Implemented ETL/data integration and consolidated datasets using SQL and AWS S3. Developed ARIMA/SARIMA-style forecasting with seasonality/trend components and moving averages. Performed customer segmentation (e.g., K-Means/RFM-style) and revenue analytics with feature selection and cross-validation. Created Tableau dashboards and KPI reporting views, and applied A/B testing and statistical diagnostics for reliability and stakeholder handoff.