Machine Learning Ops and Data Engineer

Job Description

Key Responsibilities

As a Data Platform and MLOps engineer, you will be part of our Data Platform team and play an important role in our daily operations. Your responsibilities will include:

• Deploy machine learning models into production environments and support their operational lifecycle.
• Support cloud-based analytical, reporting, and machine learning infrastructure.
• Collaborate closely with Data Science, Engineering, Risk, BI, and IT teams to align data and model requirements with production standards.
• Develop automation for model deployment, updates, scaling, and recurring data processing tasks.
• Implement monitoring for both data pipelines and machine learning models, including performance, availability, and quality checks.
• Ensure reliable operation and continuous development of the analytical data warehouse environment.
• Design, maintain, troubleshoot, and optimize ETL/data pipelines supporting reporting, analytics, and machine learning use cases.
• Ensure timely and high-quality data availability for BI, Risk, Data Science, and other business stakeholders.
• Identify, investigate, and resolve performance issues across data warehouse, ETL, and model deployment processes.
• Troubleshoot, debug, upgrade, and improve existing software, pipelines, and deployment processes.
• Gather and evaluate user feedback, recommend improvements, and execute enhancements.
• Maintain technical documentation for data processes, model deployments, configurations, and operational procedures.
  

Qualifications And Experience

We are looking for someone who has:

• 2+ years of experience in data engineering and machine learning
• Strong Python programming skills and intermediate SQL knowledge
• Good understanding of databases, data warehouse concepts, and ETL processes
• Understanding of machine learning lifecycle and model operationalization
• Using LLM’s to generate and optimize code, ability to use AI platform features to enhance and speed up workflows
• Knowledge of DevOps practices, CI/CD pipelines, and version control
• Experience with cloud-based analytical and reporting solutions, preferably Azure
• Familiarity with machine learning frameworks and tools such as scikit-learn and XGBoost
• Familiarity with containerization technologies such as Docker
• Ability to monitor, troubleshoot, and optimize data pipelines, infrastructure, and deployed models
• Experience with software design, development, debugging, and documentation

Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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