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

AI/ML Engineer with 4+ years of experience building production-grade Machine Learning, Generative AI, and Agentic AI solutions across financial services and healthcare. Experienced in developing enterprise RAG pipelines, LLM applications, predictive ML models, and cloud-native AI platforms on Azure, AWS, and GCP. Strong background in MLOps, AI governance, model evaluation, and deploying scalable AI systems that improve business outcomes in portfolio analytics, fraud detection, and financial intelligence.…AI/ML Engineer with 4+ years of experience building production-grade Machine Learning, Generative AI, and Agentic AI solutions across financial services and healthcare. Experienced in developing enterprise RAG pipelines, LLM applications, predictive ML models, and cloud-native AI platforms on Azure, AWS, and GCP. Strong background in MLOps, AI governance, model evaluation, and deploying scalable AI systems that improve business outcomes in portfolio analytics, fraud detection, and financial intelligence.

SUVIDHA SHARMA

AI Engineer, Data Scientist, Programmer, +2





AI/ML Engineer with 4+ years of experience building production-grade Machine Learning, Generative AI, and Agentic AI solutions across financial services and healthcare. Experienced in developing enterprise RAG pipelines, LLM applications, predictive ML models, and cloud-native AI platforms on Azure, AWS, and GCP. Strong background in MLOps, AI governance, model evaluation, and deploying scalable AI systems that improve business outcomes in portfolio analytics, fraud detection, and financial intelligence.…AI/ML Engineer with 4+ years of experience building production-grade Machine Learning, Generative AI, and Agentic AI solutions across financial services and healthcare. Experienced in developing enterprise RAG pipelines, LLM applications, predictive ML models, and cloud-native AI platforms on Azure, AWS, and GCP. Strong background in MLOps, AI governance, model evaluation, and deploying scalable AI systems that improve business outcomes in portfolio analytics, fraud detection, and financial intelligence.

Available to hire

AI/ML Engineer with 4+ years of experience building production-grade Machine Learning, Generative AI, and Agentic AI solutions across financial services and healthcare. Experienced in developing enterprise RAG pipelines, LLM applications, predictive ML models, and cloud-native AI platforms on Azure, AWS, and GCP.

Strong background in MLOps, AI governance, model evaluation, and deploying scalable AI systems that improve business outcomes in portfolio analytics, fraud detection, and financial intelligence.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

Work Experience

AI/ML Engineer at State Street

September 1, 2025 - Present

Architected and developed an enterprise-scale Agentic AI platform comprising 12+ autonomous AI agents for asset management, custody banking, portfolio analytics, and investment research using Python, Azure OpenAI, LangGraph, CrewAI, and Model Context Protocol (MCP), reducing manual analyst effort by 40%. Designed and implemented an enterprise Knowledge Graph RAG platform using Neo4j, GraphRAG, LlamaIndex, Pinecone, and FAISS to enable semantic search across 500K+ financial documents, improving retrieval relevance by 32%. Fine-tuned domain-specific LLMs using PEFT, LoRA, and RLHF to improve response accuracy by 22% and reduce hallucinations by 30%. Built LLM evaluation and AI observability framework using LangSmith, RAGAS, Arize AI, and MLflow to monitor factual accuracy, latency, prompt quality, and model drift, reducing response latency by 27%. Engineered AML analytics and trade surveillance pipelines with PySpark, Spark, Kafka, Databricks, and Delta Lake to reduce fraud investigatio

AI/ML Engineer at IBM

May 1, 2021 - August 31, 2024

Designed and deployed end-to-end Machine Learning and Generative AI solutions for healthcare analytics using Python, PyTorch, TensorFlow, scikit-learn, and GCP Vertex AI to improve clinical decision-making and operational efficiency. Integrated FHIR and HL7 interoperability standards with EMR/EHR systems across 15+ hospital networks, reducing data integration/mapping errors by 20%. Developed Clinical NLP and NER pipelines using BioBERT, ClinicalBERT, Hugging Face Transformers, and spaCy to extract structured clinical insights from 200K+ unstructured physician notes, reducing manual chart review time by 30%. Built and fine-tuned domain-specific LLMs using PEFT, LoRA, RAG, and LangChain for clinical summarization and knowledge retrieval, improving physician documentation efficiency by 35% while maintaining high factual accuracy. Engineered predictive ML models for disease risk prediction using XGBoost, LightGBM, and TensorFlow, improving early-stage detection of chronic cardiovascular c