AI / ML Engineer

Role Overview : Build, train, and deploy machine learning models for predictive analytics and data-driven decision making. Implement end-to-end ML pipelines from data preparation to production deployment.

Key Responsibilities

Develop and train ML models for classification, regression, forecasting, and anomaly detection

, Perform feature engineering, data preprocessing, and exploratory data analysis

• Implement model training pipelines with hyperparameter optimization
• Deploy models to production and integrate with application services
• Monitor model performance, detect drift, and trigger retraining
• Collaborate with data engineers on feature store and data pipeline design
• Conduct A / B testing and model performance evaluation
• Document model architectures, experiments, and deployment processes Required Skills Machine Learning :
• Strong foundation in supervised and unsupervised learning algorithms
• Time-series forecasting and anomaly detection techniques
• Classification, regression, clustering, and ensemble methods
• Feature engineering and feature selection strategies
• Model evaluation metrics and validation techniques
• Handling imbalanced datasets and data quality issues Statistical & Mathematical :
• Statistics, probability, and linear algebra
• Hypothesis testing and statistical inference
• Optimization algorithms and gradient descent
• Understanding of model bias, variance, and overfitting Data Processing :
• Data cleaning, transformation, and normalization
• Exploratory Data Analysis (EDA) and data visualization
• Working with structured and unstructured data
• ETL / ELT pipeline integration

Required Tech Stack Programming & ML :