Coopers iET AG
MLOps Engineer - MLFlow / Azure Databricks
Coopers iET AG, Indianapolis, Indiana, United States
For our client in the financial industry, we are looking for an
MLOps Engineer – MLFlow / Azure Databricks.
Your 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
Contribute to the design of the target MLOps architecture and assist with migration planning to Azure Databricks
Your Profile
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)
#J-18808-Ljbffr
MLOps Engineer – MLFlow / Azure Databricks.
Your 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
Contribute to the design of the target MLOps architecture and assist with migration planning to Azure Databricks
Your Profile
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)
#J-18808-Ljbffr