About
Machine Learning Engineer with +6 years of hands-on experience developing Python and machine learning solutions for industrial and production use cases. Experienced in classification, regression, clustering, NLP, exploratory data analysis, feature analysis and model interpretability using Python, Pandas, NumPy, Scikit-learn, XGBoost and TensorFlow. Built ML solutions for batch quality classification, manufacturing quality prediction, industrial fuel-consumption prediction and engineer-site assignment, with reported model accuracies of up to 95%. Currently expanding into Generative AI through hands-on work with Hugging Face, LangChain and LangGraph.
Skills & Expertise (43)
Work Experience
Technology Analyst
Infosys
Nov 2021 - Present
Develop Python and machine learning solutions for industrial and production-oriented use cases. Built a Python-based site-assignment application to assign engineers to service sites using distance, workload and annual travel history. Applied Nearest Neighbor-based logic to incorporate proximity into engineer-site assignment. Contribute to Python development and ML workflows supporting data-driven industrial applications.
Machine Learning Engineer
Modelicon Infotech
Aug 2019 - Sep 2021
Developed binary and multiclass classification models for batch-quality monitoring using simulated bioreactor data. Built a model to classify new production batches into Very Good, Good, Marginal and Poor quality categories. Achieved 95% classification accuracy on the developed solution. Applied OneHotEncoder preprocessing and Random Forest modeling. Developed a multilabel classification solution based on critical quality attributes. Achieved 92% accuracy on the developed model. Used Random Forest-based modeling and visualization to analyze quality attributes. Developed an ML solution to predict diesel fuel consumption for industrial coffee roasting cycles. Identified variables contributing to deviations in fuel consumption. Built Linear Regression and XGBoost models to predict fuel consumption for new batches. Analyzed and recreated machine-learning modeling workflows developed on the Yokogawa Industrial ML Platform. Performed EDA and feature-ranking analysis to evaluate model inputs. Applied Permutation Importance and SHAP-based analysis to interpret model behavior and identify influential features.
Education
B.Tech, Electronics & Communication Engineering - Eternal University
2008 - 2012 · Afghanistan
Data Science & AI Certification - Learnbay
- 2021 · Afghanistan
Machine Learning & Deep Learning - iNeuron
- 2021 · Afghanistan
Certifications
Data Science & AI Certification
Learnbay · 2021
Machine Learning & Deep Learning
iNeuron · 2021
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Skills (43)
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