🔥 Transforming complex problems into deployable AI solutions
Aspiring software and ML engineer skilled in developing and deploying scalable machine learning systems with MLOps , cloud experience, and solid foundation in algorithms.
Open to: SDE | ML Engineering | MLOps roles
graph LR
A[Business<br>Objective] --> B{Problem<br>Analysis}
B --> C[Data<br>Acquisition]
B --> D[Algorithm<br>Selection]
C --> E[Feature<br>Engineering]
D --> E
E --> F[Model<br>Development]
F --> G[Validation<br>Metrics]
G --> H[Deployment<br>Strategy]
H --> I[Monitoring<br>& CI/CD]
I --> J[Stakeholder<br>Communication]
J --> A
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• Clustered 8.9k users (0.7 silhouette score) identifying 4 customer personas • Built interactive dashboard driving 25%↑ campaign ROI and 18%↑ retention • Reduced default risk by 30% through credit profiling insights |
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• End-to-end risk pipeline with 91% ROC-AUC and SHAP explainability • Containerized on AWS (EC2/S3/ECR) with CI/CD automation • Reduced evaluation time by 80% while increasing accuracy by 25% |
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• Robust pipeline with drift detection achieving 94% precision • Version control via MLflow + DAGsHub for team collaboration • Real-time inference on AWS with automated CI/CD pipelines |
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• Custom Seq2Seq model with domain-specific tuning • Reproducible workflows via DVC and MLflow • Deployed on AWS achieving 90%+ accuracy for chatbot integration |
| Education | Certifications |
|---|---|
| Muffakham Jah College of Engineering B.E. Information Technology CGPA: 8.0/10 • 2021-2025 |
• Complete Data Science & ML - Udemy • MLOps with 10+ Projects - Udemy • AI Curriculum - NASSCOM • AWS Machine Learning - In Progress • Soft Skills - TCS iON |