Skip to Content
Role page

Machine Learning Engineer

I build and ship models that turn messy data into reliable decisions. I focus on the full path from data preparation to evaluation to deployment friendly outputs, with careful assumptions and clear metrics.

What I deliver

  • Predictive models with measurable lift and clear baselines
  • Reproducible pipelines in Python with clean feature logic
  • Evaluation that explains tradeoffs, not just accuracy numbers
  • Documentation and structure suitable for real stakeholders

Core strengths

Model development

  • Classification, regression, forecasting
  • Feature engineering and error analysis
  • Versioned iterations

Applied ML domains

  • NLP and text classification
  • Computer vision and image understanding
  • Real world constraints and defensible results

Selected MLE projects

Curated for Machine Learning Engineer roles. It excludes pure dashboard work and keeps projects that show modeling and systems thinking.

Visual Question Answering (VQA) System for Medical Images

2024

Visual Question Answering (VQA) for medical images is an advanced task in the field of medical imaging and artificial intelligence. This project aims to bridge the gap between…

  • Python
  • JavaScript
  • CSS
  • HTML