Machine Learning Engineer

Key responsibilities:

• Support and monitor weekend batch loads, ensuring timely and accurate execution
• Perform outlier detection and root cause analysis for issues such as demand forecast drops or anomalies
• Translate findings into clear insights and communicate them effectively to leads and stakeholders
• Monitor scheduled jobs and data pipelines to ensure successful execution
• Validate dashboard outputs and analyze data trends, anomalies, and inconsistencies
• Support basic model validation and output analysis (e.g., forecast vs actuals, error trends)
• Write and optimize SQL queries and PySpark transformations for debugging and analysis
• Identify patterns in recurring failures and recommend improvements
• Work with data science and engineering teams to debug model or data-related issues
• Escalate issues when required, with clear analysis and supporting insights
• Monitor workflows in Azure Data Factory (ADF) and Databricks
• Contribute to CI/CD validation and release monitoring
• Maintain documentation for issues, RCA findings, and fixes

Tech stack required:

• 4 to 10 years of experience as Machine Learning Engineer
• Strong working knowledge of SQL (must-have)
• Basic to intermediate PySpark / Python
• Understanding of data pipelines and distributed data processing
• Familiarity with Azure Data Factory (ADF) and Databricks
• Basic understanding of machine learning workflows and model outputs
• Ability to perform data analysis and debugging using data
• Exposure to CI/CD processes and Azure DevOps