To design, implement, and manage machine learning infrastructure that supports scalable and reliable deployment of machine learning models.

MLOps Engineer

Your responsibilities

• Design and build CI/CD pipelines for machine learning models.
• Manage and optimize ML model deployment and performance.
• Automate and monitor model retraining processes.
• Ensure data quality and compliance with data governance policies.
• Collaborate with data scientists to integrate models into production environments.
• Develop and maintain infrastructure for data ingestion and feature engineering.
• Troubleshoot and resolve issues related to ML infrastructure and platforms.

Our requirements

• Bachelor's degree in Computer Science, Data Science, or related field.
• Proficiency in programming languages such as Python and/or Java.
• Experience with machine learning frameworks and libraries.
• Knowledge of containerization technologies like Docker and Kubernetes.
• Familiarity with version control systems such as Git.
• Strong problem-solving and troubleshooting skills.
• Ability to work as part of a team and communicate effectively.
• Experience with cloud platforms (e.g., AWS, GCP, Azure).
• Knowledge of MLOps principles and best practices.
• Familiarity with infrastructure-as-code tools (e.g., Terraform).
• Experience with monitoring and logging tools (e.g., Prometheus, Grafana).
• Understanding of data engineering principles and tools.
• Domain knowledge in relevant industry applications.