Sai Krishna Kompelly
Sai Krishna Kompelly is a Lead AI Engineer, Bilvantis Technologies, with 5 years in the industry.
Machine learning engineer who builds production ML and generative AI systems for banking, healthcare and enterprise clients, and trains engineers in the full model lifecycle.
Sai Krishna Kompelly is a machine learning engineer and data scientist based in Hyderabad, working across the full model lifecycle: exploratory data analysis, feature engineering, model training and validation, and getting models into production. The work spans classical machine learning, deep learning, time-series forecasting, anomaly detection and retrieval-augmented generative AI, with MLOps practice built around MLflow experiment tracking and model registries.
Current role
- Lead AI Engineer, Bilvantis Technologies (since September 2024) — builds AI systems for enterprise clients, including an international bank, covering anomaly detection, LLM-assisted code review and RAG-based document intelligence.
Earlier experience
- Data Engineer, Sail Analytics, Bangalore (2023–2024) — data pipelines, forecasting models and generative AI applications for healthcare, retail and manufacturing clients.
- Machine Learning Engineer, upGrad INSOFE, Hyderabad (2021–2023) — built and evaluated ML models on healthcare and education data, and mentored junior engineers through hands-on training in EDA, feature engineering, ML pipelines, experiment tracking, validation and deployment.
What learners get
A practitioner’s view of how machine learning is actually done at work: starting every project with careful EDA and feature engineering, validating models properly before trusting them, and tracking, versioning and deploying them so they keep working after launch. The examples come from real healthcare, finance and enterprise automation projects.
Areas of expertise
- Machine learning (Random Forest, XGBoost, LightGBM, SVM, clustering)
- Deep learning with PyTorch and TensorFlow (LSTM/GRU, CNNs, autoencoders)
- Exploratory data analysis and feature engineering
- Model training, cross-validation and hyperparameter tuning
- Time-series forecasting (ARIMA, SARIMA, Prophet, LSTM)
- Anomaly detection
- MLOps with MLflow, Docker, Jenkins and Azure ML
- Generative AI: LangChain, RAG pipelines and LLM fine-tuning
- Data engineering with Spark, Hadoop and SQL
- OCR and NLP document intelligence
Achievements
- 5 years building and deploying machine learning systems across banking, healthcare, finance, retail and enterprise automation
- Built production RAG and generative AI platforms combining OCR, knowledge graphs and vector search
- Delivered document-extraction pipelines reaching 95% to 99%+ accuracy for healthcare, packaging and invoice-processing clients
- Mentored junior engineers and ran hands-on training in EDA, feature engineering, ML pipelines, MLflow and deployment at upGrad INSOFE
Education
- Post Graduate Program in Computational Data Science, Case Western Reserve University and INSOFE (2022)
- B.Tech in Electrical and Electronics Engineering, Geethanjali College of Engineering & Technology (2022)
Certifications
- Postgraduate Certificate in Computational Data Science, INSOFE and Case Western Reserve University
- Machine Learning Pipelines with Azure ML Studio, Coursera
- Machine Learning Certification, LinkedIn Learning
- Python and R Programming Certifications, LinkedIn Learning
- Python for Beginners, Electronics & ICT Academy, IIT Roorkee
- Programming for Everybody, University of Michigan (Coursera)