Machine Learning Engineer हायर करें

ML Engineers focus specifically on the model development lifecycle — feature engineering, algorithm selection, hyperparameter tuning, and model validation. AI Engineers have a broader scope including system architecture, deployment infrastructure, and integration with business applications.

Our ML Engineers build classification, regression, clustering, recommendation, time-series forecasting, and anomaly detection models. They work with both traditional ML (XGBoost, Random Forest) and deep learning (transformers, CNNs, RNNs) depending on the problem.

Every model goes through rigorous validation: cross-validation, holdout testing, and domain-specific evaluation metrics. We also implement model monitoring in production to detect data drift, performance degradation, and bias — with automated retraining triggers.

Yes. Our ML Engineers integrate with your existing data warehouses (Snowflake, BigQuery, Redshift), feature stores, and MLOps platforms. They adapt to your tech stack rather than forcing a new one.