Senior Machine Learning Engineer (Classical ML & MLOps)

About the Role

We are seeking a Senior Machine Learning Engineer with strong expertise in classical machine learning algorithms , model optimization , and end-to-end MLOps deployment .

You will design, build, and operationalize scalable ML pipelines and ensure that ML models transition smoothly from experimentation to production. The ideal candidate combines deep technical skills with hands-on experience in automating and maintaining ML systems at scale.

Key Responsibilities

Machine Learning Development

• Design, train, and validate classical ML models (regression, tree-based models, ensemble methods, clustering, anomaly detection, etc.) for structured / tabular datasets.
• Collaborate with data scientists and data engineers to translate analytical models into production-grade code .
• Perform feature engineering, model tuning, and evaluation using frameworks like Scikit-learn, XGBoost, LightGBM, or CatBoost.
• Analyze data quality, perform exploratory data analysis (EDA), and create reusable feature stores.

MLOps & Productionization

Skills Required

Jenkins, Docker, ECS, XGBoost, Kubernetes