Machine Learning (ML) Engineer

About the Role

We are looking for an experienced ML Engineer to build, deploy and maintain scalable machine learning models and pipelines. The ideal candidate should have strong foundations in machine learning, Python, PySpark and MLOps, along with hands-on experience deploying models in production environments

Required Technical Skills

• Strong Python programming.
• Hands-on experience with Machine Learning algorithms.
• Experience with Scikit-learn, PyTorch or TensorFlow.
• Strong understanding of statistics, feature engineering and model validation.
• Experience with Pandas, NumPy and SQL.
• Hands-on experience with PySpark and Apache Spark.
• Experience with MLflow and MLOps.
• Exposure to Databricks ML workflows and production model deployment.
• Knowledge of Azure, AWS or GCP.
• Experience with model monitoring and performance optimization.

Key Responsibilities

• Design, develop and deploy machine learning models.
• Build end-to-end ML pipelines covering data preparation, feature engineering, training and inference.
• Develop predictive models for forecasting, classification, recommendation and personalization.
• Work with structured and unstructured datasets.
• Perform model selection, validation, hyperparameter tuning and optimization.
• Implement MLOps practices for model tracking, versioning, deployment and monitoring.
• Use MLflow for experiment tracking, model registry and model serving.
• Develop scalable data processing workflows using Python and PySpark.
• Monitor model performance, detect drift and improve model accuracy.
• Collaborate with data scientists, data engineers and business stakeholders