AI Engineer with 6 years of experience developing intelligent AI applications using Machine Learning, Deep Learning, Generative AI, Large Language Models, NLP, Computer Vision, and predictive analytics. Experienced in building production-ready AI solutions, deploying scalable ML pipelines, and integrating AI capabilities into enterprise platforms using Python, PyTorch, LangChain, cloud services, and modern MLOps practices.
Expertise & skills
Programming
PythonSQLJava
AI & ML
Machine LearningDeep LearningNLPComputer VisionGenerative AILLMs
Frameworks
PyTorchTensorFlowScikit-learnLangChainLlamaIndexHugging Face
Vector Databases
WeaviateFAISSChromaDB
Cloud
AWSMicrosoft Azure
Databases
PostgreSQLMongoDB
DevOps
DockerKubernetesMLflowGitHub Actions
Visualization
Power BITableau
Selected projects
Technologies: Python, LangChain, Azure OpenAI, ChromaDB, FastAPI
- Built an AI assistant for clinical knowledge retrieval.
- Implemented RAG for evidence-based responses.
- Integrated secure APIs with hospital applications.
- Improved information retrieval accuracy.
- Optimized prompt templates for medical queries.
- Developed scalable backend services.
Technologies: Python, PyTorch, Pandas, XGBoost, AWS
- Developed demand forecasting models for retail products.
- Performed feature engineering on historical sales data.
- Built automated model retraining pipelines.
- Reduced stock shortages through accurate forecasting.
- Published prediction APIs for downstream systems.
- Created monitoring dashboards.
Technologies: Python, NLP, Hugging Face, FastAPI
- Built AI-powered resume ranking engine.
- Extracted candidate skills using NLP.
- Implemented semantic matching with job descriptions.
- Reduced recruiter screening time significantly.
- Integrated REST APIs with HR platform.
- Improved candidate ranking quality.
Technologies: Python, OpenCV, TensorFlow, Docker
- Developed computer vision models for quality inspection.
- Automated defect classification on production lines.
- Improved detection precision using CNN models.
- Containerized deployment using Docker.
- Reduced manual inspection workload.
- Supported real-time image inference.
Ways of working
LeadershipCommunicationProblem SolvingCollaborationCritical ThinkingAgile Development
Certifications
- Google Professional Machine Learning Engineer
- Microsoft Certified: Azure AI Engineer Associate
- DeepLearning.AI NLP Specialization
- AWS Certified AI Practitioner
Education
Bachelor of Engineering in Computer Engineering
Visvesvaraya Technological University
Achievements
- Delivered 18+ enterprise AI solutions.
- Improved AI model accuracy by up to 18% through feature engineering.
- Built reusable LLM components across multiple projects.
- Optimized inference performance for production workloads.
- Mentored junior developers in AI solution development.
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