Looks like you have JavaScript disabled. For the full Twine experience, you will need to re-enable it.

Senior AI/ML Engineer with 10 years of experience delivering enterprise AI/ML, NLP, and automation solutions. Strong expertise in LLMs, transformer models, RAG, multimodal AI, and production-grade NLP systems. Hands-on experience across data engineering, model training, evaluation, deployment, and monitoring pipelines. Built secure GenAI platforms using Amazon Bedrock, Azure OpenAI, LangChain, vector search, and prompt engineering; optimized inference with GPU acceleration and production-ready LLMOps.…Senior AI/ML Engineer with 10 years of experience delivering enterprise AI/ML, NLP, and automation solutions. Strong expertise in LLMs, transformer models, RAG, multimodal AI, and production-grade NLP systems. Hands-on experience across data engineering, model training, evaluation, deployment, and monitoring pipelines. Built secure GenAI platforms using Amazon Bedrock, Azure OpenAI, LangChain, vector search, and prompt engineering; optimized inference with GPU acceleration and production-ready LLMOps.

Sushma

AI Engineer, Data Scientist, Developer, +3





Senior AI/ML Engineer with 10 years of experience delivering enterprise AI/ML, NLP, and automation solutions. Strong expertise in LLMs, transformer models, RAG, multimodal AI, and production-grade NLP systems. Hands-on experience across data engineering, model training, evaluation, deployment, and monitoring pipelines. Built secure GenAI platforms using Amazon Bedrock, Azure OpenAI, LangChain, vector search, and prompt engineering; optimized inference with GPU acceleration and production-ready LLMOps.…Senior AI/ML Engineer with 10 years of experience delivering enterprise AI/ML, NLP, and automation solutions. Strong expertise in LLMs, transformer models, RAG, multimodal AI, and production-grade NLP systems. Hands-on experience across data engineering, model training, evaluation, deployment, and monitoring pipelines. Built secure GenAI platforms using Amazon Bedrock, Azure OpenAI, LangChain, vector search, and prompt engineering; optimized inference with GPU acceleration and production-ready LLMOps.

Available to hire

Senior AI/ML Engineer with 10 years of experience delivering enterprise AI/ML, NLP, and automation solutions. Strong expertise in LLMs, transformer models, RAG, multimodal AI, and production-grade NLP systems.

Hands-on experience across data engineering, model training, evaluation, deployment, and monitoring pipelines. Built secure GenAI platforms using Amazon Bedrock, Azure OpenAI, LangChain, vector search, and prompt engineering; optimized inference with GPU acceleration and production-ready LLMOps.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Language

English

Advanced

Hindi

Intermediate

Work Experience

Senior AI Engineer / Agentic AI at Cigna Healthcare

April 1, 2025 - Present

Architected and fine-tuned LLMs with Amazon Bedrock using transformers and LoRA for secure enterprise use cases. Engineered RAG pipelines with LangChain and vector search to improve search precision and grounded responses. Built healthcare assistants supporting claims processing, prior authorization, provider knowledge search, and member service workflows. Implemented AI safety via adversarial testing, prompt injection mitigations, guardrails, and output validation. Led LLMOps including monitoring, drift detection, prompt governance, and output validation for reliable production releases. Developed HIPAA-compliant GenAI apps with secure PHI handling, encryption, and enterprise governance. Built FastAPI and GraphQL inference APIs, reducing query latency by 40%. Optimized distributed inference using TorchServe, Ray, GPU acceleration, and batching; reduced multimodal AI latency by 35% and lowered cloud cost by 20%. Designed cloud-native AI infrastructure using AWS CloudFormation/CDK and d

Senior AI Engineer at Cigna Health Care

April 1, 2025 - Present

Architected and fine-tuned LLMs with Amazon Bedrock, transformers, and LoRA for secure enterprise AI use cases. Engineered RAG pipelines using LangChain and vector search to improve retrieval precision and grounded responses. Built healthcare assistants for claims processing, prior authorization, provider knowledge search, and member service workflows. Implemented AI safety controls including adversarial testing, prompt injection mitigation, guardrails, and output validation. Led LLMOps with monitoring, drift detection, prompt governance, and reliable production releases. Developed HIPAA-compliant GenAI applications with secure PHI handling, encryption, and enterprise governance. Built FastAPI/GraphQL inference APIs and optimized latency via serving and distributed inference (Ray, TorchServe, GPU acceleration, batching). Orchestrated repeatable training/evaluation/deployment pipelines using SageMaker and Step Functions, and deployed models on Lambda/ECS/EKS/Fargate with autoscaling and

Senior Data Scientist / ML Engineer / GenAI Engineer at CapitalOne

January 1, 2024 - March 31, 2025

Built Spark and Kafka pipelines for real-time processing of 2M+ events/day with 99.9% reliability. Designed enterprise LLM/GPT solutions using Hugging Face Transformers and Azure OpenAI for healthcare use cases. Developed NLP workflows including summarization, sentiment analysis, and NER. Accelerated inference using GPU optimization, ONNX, and TensorRT to improve speed and deployment efficiency. Refined prompt engineering and response controls for output quality, accuracy, and consistency. Delivered RAG pipelines using LangChain, LlamaIndex, and FAISS for contextual search and grounded enterprise answers. Built Flask REST APIs to provide reusable model access across microservices. Implemented document intelligence solutions for loan/account documentation and regulatory reports using OCR, LLMs, and RAG. Added Responsible AI controls such as prompt guardrails, content filtering, audit logging, and human-in-the-loop validation for regulated environments. Performed evaluation/A-B testing a

Senior Data Scientist / ML Engineer / GenAI Engineer at State of CA (CA-MMIS)

January 1, 2021 - December 31, 2023

Built Spark and Kafka pipelines supporting real-time processing of 2M+ events/day with 99.9% reliability. Developed secure enterprise healthcare NLP and GenAI solutions using Azure OpenAI and Hugging Face Transformers. Implemented NLP tasks (summarization, sentiment analysis, NER) and designed prompt engineering strategies to improve accuracy and reduce hallucinations. Accelerated inference using GPU optimization, ONNX, and TensorRT. Built RAG pipelines with LangChain/LlamaIndex/FAISS for contextual, grounded answers. Delivered AI/ML services as Flask REST APIs for reuse across microservices. Conducted evaluation and hyperparameter tuning; built scalable solutions with Azure Databricks, Azure ML Studio, Azure Functions, and Azure Logic Apps. Containerized workflows with Docker and deployed on Kubernetes/AKS. Strengthened security using RBAC, Azure Key Vault, encryption, and audit logging, reducing compliance risk. Automated testing/versioning/deployment with Azure DevOps CI/CD and LLMO

Data Scientist / Machine Learning Engineer at Blue Yonder

December 1, 2017 - December 31, 2019

Delivered classification, regression, and recommendation solutions improving forecasting accuracy by 22% and enhancing enterprise marketing segmentation. Applied feature engineering, hyperparameter optimization, and model tuning to improve precision/recall by 20%+ across predictive analytics initiatives. Integrated ML models with RESTful APIs and cloud-native applications for real-time prediction services. Leveraged AWS (EC2, S3, Lambda, SageMaker) to build/train/deploy/manage scalable ML workloads. Partnered with data engineering and software teams for end-to-end pipelines including automated ingestion, training, and continuous retraining. Built NLP solutions for text preprocessing, tokenization, sentiment analysis, and document classification. Engineered scalable data processing with PySpark/Spark for high-volume structured and semi-structured datasets. Designed, trained, validated, and deployed models using Python, scikit-learn, TensorFlow, and XGBoost. Automated ETL, data quality c

Data Scientist / Machine Learning Engineer at Blue Yonder (Client: Citibank-Singapore)

December 1, 2017 - December 31, 2019

Delivered machine learning solutions for classification, regression, and recommendation systems improving forecasting accuracy by 22% and enhancing customer segmentation. Applied feature engineering, hyperparameter optimization, and model tuning to improve precision and recall by 20%+. Integrated ML models with REST APIs and cloud-native applications for real-time predictions and automated business processes. Built and managed scalable ML workloads on AWS using EC2, S3, Lambda, and SageMaker. Partnered with data engineering and software teams to implement end-to-end ML pipelines for ingestion, training, and continuous retraining. Developed NLP solutions for preprocessing, tokenization, sentiment analysis, and document classification. Built scalable data processing using PySpark and Spark for high-volume datasets. Designed, trained, validated, and deployed predictive models using Python, scikit-learn, TensorFlow, and XGBoost. Automated ETL and data quality checks using Python and SQL. E

Data Scientist / Machine Learning Engineer at Blue Yonder (Citibank-Singapore client)

December 1, 2017 - December 31, 2019

Delivered ML solutions for classification, regression, and recommendation systems, improving forecasting accuracy by 22% and enhancing customer segmentation. Applied feature engineering, hyperparameter optimization, and model tuning to improve precision and recall by 20%+ across predictive analytics initiatives. Integrated models with REST APIs and cloud-native applications for real-time prediction services and automated business processes. Leveraged AWS (EC2, S3, Lambda, SageMaker) to build/train/deploy and manage scalable ML workloads. Partnered with data engineering and software teams to design end-to-end ML pipelines for automated ingestion, training, and continuous retraining. Built NLP solutions for preprocessing, tokenization, sentiment analysis, and document classification using Python NLP libraries. Engineered scalable data processing with PySpark/Spark. Designed, trained, validated, and deployed models with Python, scikit-learn, TensorFlow, and XGBoost. Automated ETL, data qu

Data Scientist / Machine Learning Engineer - Python at OSI Digital

August 1, 2014 - November 30, 2017

Extracted, integrated, and analyzed data from MySQL and SQL Server using advanced SQL for accurate reporting. Used Apache Spark and Hadoop to process and analyze large-scale datasets. Collaborated with stakeholders to gather requirements and deliver actionable insights. Designed, trained, and evaluated classification models (Logistic Regression, Decision Trees, Random Forest). Automated recurring data preparation/validation/reporting workflows with Python, reducing manual effort by ~65% and improving turnaround times. Performed EDA and statistical assessments on millions of records to identify trends. Prepared and standardized structured/semi-structured data using Python and Microsoft Excel. Built predictive analytics solutions with pandas, NumPy, and scikit-learn. Contributed to ML design/validation/deployment in Agile teams and managed experimentation via Jupyter and GitHub. Developed KPI-driven dashboards and executive reports using Tableau and Seaborn.

Data Scientist / Machine Learning Engineer at OSI Digital

August 1, 2014 - November 30, 2017

Extracted and integrated data from MySQL and SQL Server using advanced SQL for reporting and decision-making. Used Apache Spark/Hadoop for distributed processing of large datasets. Gathered analytical requirements and translated business objectives into technical solutions. Designed/trained/evaluated ML models (Logistic Regression, Decision Trees, Random Forest) to improve classification and predictive performance. Automated recurring data preparation/validation/reporting with Python, reducing manual effort by ~65% and improving turnaround time. Conducted EDA and statistical analysis on millions of records. Prepared and standardized structured/semi-structured data using Python and Microsoft Excel. Built forecasting/trend analysis solutions using pandas/NumPy/scikit-learn. Collaborated in Agile teams for ML model validation and deployment support. Used Jupyter Notebook and GitHub for version-controlled experiments and documentation. Developed KPI-driven dashboards and executive reports