Our company is seeking a skilled MLOps Engineer to join our team. As an MLOps Engineer, you will be responsible for designing and implementing data pipelines, machine learning models, and automation workflows.
Key Responsibilities:
* Set up and configure MLFlow tracking, model registry, and artifact storage for both on-prem and Azure environments.
* Integrate MLFlow with Databricks and/or on-premise infrastructure.
* Ensure secure access, data protection, and compliance with internal policies and governance standards.
* Enable MLOps automation by supporting CI/CD pipelines for ML models using tools such as Azure DevOps or GitHub Actions.
* Define and implement workflows for model training, validation, deployment, and monitoring.
* Collaborate closely with data scientists and platform engineers to operationalize machine learning models effectively.
* Produce detailed documentation of setup processes, workflows, and best practices.
Required Skills and Qualifications:
* Proven hands-on experience with MLFlow, both on-premise and in cloud environments.
* Good understanding of Azure Databricks and its MLFlow integration.
* Strong background in MLOps tooling, including CI/CD, model lifecycle management, and monitoring.
* Familiarity with security, governance, and compliance within ML workflows.
* Excellent communication and technical documentation skills.
* Fluent in English (written and spoken).
Benefits:
You will have the opportunity to work with a talented team of professionals and contribute to the development of cutting-edge AI solutions.
Others:
This role requires a strong passion for machine learning and a willingness to continuously learn and adapt to new technologies.