Sravani Koyya
AI/ML Engineer | Generative AI & LLMs (RAG, LangChain, LangGraph) | NLP & Deep Learning | MLOps | AWS, GCP, Azure
- Role
- Ai Ml Engineer at Honeywell Technologies
- Location
- Jersey City, NJ, US
- LinkedIn followers
- 500 followers
About Sravani Koyya
I am an AI/ML Engineer with 4+ years of experience building scalable machine learning and generative AI solutions across industrial analytics and document intelligence. I design end-to-end ML pipelines, develop deep learning and NLP models, and deploy production-ready AI systems using Python, PyTorch, and TensorFlow. Recently, I’ve been focusing on LLM-powered applications like RAG pipelines, semantic search, and AI assistants using LangChain and LangGraph, along with vector databases such as FAISS and Pinecone. I enjoy solving real-world problems—from predicting equipment failures using IoT data to enabling intelligent document analysis—and I have hands-on experience with MLOps and cloud platforms like AWS, GCP, and Azure to deliver reliable, scalable AI systems.
Experience
Ai Ml Engineer
Feb 2026 — Present
Spearheaded development of the Industrial Predictive Maintenance Intelligence Platform by building machine learning pipelines using Python, PyTorch, and time-series forecasting techniques to predict equipment failures from industrial sensor telemetry.• Designed deep learning models and anomaly detection algorithms using TensorFlow and Scikit-learn to identify abnormal equipment behavior from IoT sensor streams, improving early fault detection accuracy by 27%.• Implemented scalable data processing and feature engineering pipelines using PySpark, Airflow, and BigQuery to integrate high-volume operational datasets and improve predictive maintenance model training efficiency by 30%.• Deployed AI inference services and LangChain-based RAG-enabled diagnostic assistants using FastAPI, Docker, and AWS SageMaker to deliver real-time insights and automated troubleshooting recommendations for engineering teams.• Developed automated model monitoring and drift detection pipelines using MLflow and cloud monitoring tools to track model performance and ensure reliable production AI deployments.
Education
Pace University - Seidenberg School of Computer Science and Information Systems
Master of Science - MS, Computer Science
Gayatri Vidya Parishad College of Engineering for Women
B. Tech , Information Technology
2017 — 2021
Find verified contacts for anyone on LinkedIn
Unifers gives sales teams verified emails and direct dials, enriched profiles, and outreach that lands in the inbox.
Free plan included · No credit card required
This profile is compiled from publicly available professional sources. Unifers is not affiliated with or endorsed by LinkedIn. Request removal of this profile.