As a results-driven Machine Learning Engineer with over 4 years of experience, I specialize in designing, developing, and deploying robust ML solutions at scale. My passion lies in transforming data into actionable insights and intelligent products. I thrive in cross-functional teams and love tackling real-world challenges using state-of-the-art ML and AI techniques.

• 💡 Proven track record in end-to-end ML product development—data pipelines, model training, deployment, and monitoring
• 🏆 Delivered impactful projects in Computer Vision, NLP, and Predictive Analytics
• 🚀 Advocate for MLOps best practices and scalable, production-grade solutions
• 🤝 Open-source contributor and lifelong learner, always exploring the latest in AI/ML

Languages: Python, SQL
Frameworks: PyTorch, TensorFlow, scikit-learn, XGBoost, FastAPI, Flask
Data & Visualization: Pandas, NumPy, Matplotlib, Seaborn
Deployment & MLOps: Docker, Kubernetes, CI/CD, MLflow, DVC, Airflow
Cloud: AWS (SageMaker, Lambda), GCP (Vertex AI), Azure ML
Specialties: Computer Vision, NLP, Model Optimization, Model Monitoring

• Intelligent Image Classification System: Reduced manual effort by 70% for a global retailer using deep learning and automated pipelines.
• End-to-End NLP Platform: Built a scalable text analytics pipeline for sentiment analysis and topic modeling, powering business insights used by 100k+ users.
• MLOps Automation: Designed reusable CI/CD templates and monitoring dashboards, cutting deployment time by 40%.