AI Engineer with 6 years of experience building enterprise AI solutions using Machine Learning, Deep Learning, Generative AI, Large Language Models (LLMs), NLP, Computer Vision, and MLOps. Skilled in designing scalable AI applications, intelligent automation platforms, conversational AI, predictive analytics, and cloud-native AI deployments.
Expertise & skills
Programming Languages
PythonSQLJavaScript
AI Technologies
Machine LearningDeep LearningNLPComputer VisionGenerative AIPredictive Analytics
LLM & AI Frameworks
LangGraphLangChainCrewAIHugging FaceOpenAI APIGemini API
ML Frameworks
PyTorchTensorFlowScikit-learnCatBoost
Vector Databases
PineconeMilvusFAISS
Cloud
AWSGoogle Cloud
Databases
PostgreSQLMongoDBRedis
DevOps & MLOps
DockerKubernetesMLflowGitHub Actions
Visualization
Power BIPlotly
Selected projects
Technologies: Python, CatBoost, PostgreSQL, FastAPI, AWS
- Developed AI models for real-time fraud detection.
- Built feature engineering pipelines for transaction analysis.
- Designed REST APIs for fraud prediction services.
- Improved fraud detection accuracy using ensemble learning.
- Automated model retraining workflows.
- Created dashboards for fraud monitoring.
Technologies: Python, LangGraph, OpenAI API, Pinecone
- Built an AI solution for legal document search and summarization.
- Implemented Retrieval-Augmented Generation for contextual responses.
- Integrated vector search for semantic retrieval.
- Optimized prompts for contract analysis.
- Developed secure APIs for enterprise applications.
- Reduced document review effort significantly.
Technologies: Python, TensorFlow, Pandas, Power BI
- Built predictive models for network outage forecasting.
- Processed large-scale telecom operational data.
- Created automated ML pipelines.
- Improved maintenance planning through predictive analytics.
- Generated executive reporting dashboards.
- Enhanced operational efficiency.
Technologies: Python, OpenCV, PyTorch, Docker
- Developed computer vision models for inventory monitoring.
- Implemented object detection for warehouse operations.
- Optimized image inference for production deployment.
- Containerized AI services using Docker.
- Integrated with warehouse management systems.
- Reduced manual inventory verification.
Ways of working
LeadershipCommunicationTeam CollaborationAnalytical ThinkingProblem SolvingAgile Methodologies
Certifications
- AWS Certified Machine Learning – Specialty
- Microsoft Certified: Azure AI Engineer Associate
- Databricks Certified Machine Learning Professional
- Google Generative AI Fundamentals
Education
Bachelor of Technology in Information Technology
SRM Institute of Science and Technology
Achievements
- Delivered more than 20 AI and Machine Learning solutions.
- Reduced model inference latency by 35% through optimization.
- Implemented reusable AI components across enterprise projects.
- Improved prediction accuracy through advanced feature engineering.
- Mentored junior AI engineers on MLOps and LLM application development.
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