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

I am an AI/ML Engineer with 5+ years of experience developing reinforcement learning, language models, and predictive analytics solutions across finance and healthcare. I design RAG pipelines, fine-tune transformer models with LoRA and Hugging Face, and build scalable inference services with FastAPI, LangChain, and AWS ECS. I’ve delivered production-grade outcomes, cutting data-retrieval latency by 80%+, automating insurance document workflows, and scaling patient-risk prediction pipelines for real-time decision support. I collaborate with risk, compliance, and clinical teams to translate unstructured data into actionable insights.…I am an AI/ML Engineer with 5+ years of experience developing reinforcement learning, language models, and predictive analytics solutions across finance and healthcare. I design RAG pipelines, fine-tune transformer models with LoRA and Hugging Face, and build scalable inference services with FastAPI, LangChain, and AWS ECS. I’ve delivered production-grade outcomes, cutting data-retrieval latency by 80%+, automating insurance document workflows, and scaling patient-risk prediction pipelines for real-time decision support. I collaborate with risk, compliance, and clinical teams to translate unstructured data into actionable insights.

Sravya Sri Datla

AI Engineer, Data Scientist, Full Stack Developer, +2





I am an AI/ML Engineer with 5+ years of experience developing reinforcement learning, language models, and predictive analytics solutions across finance and healthcare. I design RAG pipelines, fine-tune transformer models with LoRA and Hugging Face, and build scalable inference services with FastAPI, LangChain, and AWS ECS. I’ve delivered production-grade outcomes, cutting data-retrieval latency by 80%+, automating insurance document workflows, and scaling patient-risk prediction pipelines for real-time decision support. I collaborate with risk, compliance, and clinical teams to translate unstructured data into actionable insights.…I am an AI/ML Engineer with 5+ years of experience developing reinforcement learning, language models, and predictive analytics solutions across finance and healthcare. I design RAG pipelines, fine-tune transformer models with LoRA and Hugging Face, and build scalable inference services with FastAPI, LangChain, and AWS ECS. I’ve delivered production-grade outcomes, cutting data-retrieval latency by 80%+, automating insurance document workflows, and scaling patient-risk prediction pipelines for real-time decision support. I collaborate with risk, compliance, and clinical teams to translate unstructured data into actionable insights.

Available to hire

I am an AI/ML Engineer with 5+ years of experience developing reinforcement learning, language models, and predictive analytics solutions across finance and healthcare. I design RAG pipelines, fine-tune transformer models with LoRA and Hugging Face, and build scalable inference services with FastAPI, LangChain, and AWS ECS.

I’ve delivered production-grade outcomes, cutting data-retrieval latency by 80%+, automating insurance document workflows, and scaling patient-risk prediction pipelines for real-time decision support. I collaborate with risk, compliance, and clinical teams to translate unstructured data into actionable insights.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Work Experience

AIML Engineer at Morgan Stanley

August 1, 2024 - Present

Engineered RAG pipelines using LangChain, FAISS, and OpenAI GPT-4 to power internal research assistants; cut analyst document-retrieval latency from 22 s to under 4 s while maintaining 99% semantic match accuracy.

GenAI Engineer at MetLife

January 1, 2024 - July 1, 2024

Designed an enterprise-scale GenAI framework using LangChain, GPT-4, and Pinecone to process policy and claim narratives; powered retrieval-augmented responses for 12K+ weekly internal queries with 94% precision. Built a prompt-engineering layer in Python (FastAPI) to design, test, and version multi-role prompts for adjusters, underwriters, and auditors; optimized context windows and token usage, reducing hallucination rate by 41%.

Machine Learning Engineer at Space Infolab

May 1, 2019 - June 1, 2023

Built predictive models in Python (scikit-learn, XGBoost) on EHR and claims data to identify high-risk patient cohorts for readmission; improved early-intervention accuracy by 26%. Designed end-to-end ML pipelines in Airflow and Azure ML for patient outcome forecasting, automating feature generation and model retraining; cut model refresh time from 6 hours to under 45 minutes. Deployed deep learning models (CNN + TensorFlow) for imaging-based diagnosis of diabetic retinopathy, achieving 91% F1-score and integrating outputs into clinicians’ Power BI dashboards for real-time review.