3 months ago
Responsibilities
- Design and improve MLOps platform components for the model lifecycle.
- Create reusable templates and standardized pipelines for efficiency.
- Implement deployment patterns for credit risk models.
- Build and maintain CI/CD pipelines using Jenkins and GitHub.
- Automate environment configuration with Ansible.
- Implement monitoring for model performance and operational health.
- Establish dashboards and alerting systems for stakeholders.
- Mentor junior team members and contribute to engineering standards.
Requirements
- 5+ years of experience in MLOps/DevOps/Platform Engineering.
- Strong experience with CI/CD and automation using Jenkins and GitHub.
- Proficient in Airflow, Bash, and Groovy for pipeline automation.
- Hands-on experience with Ansible for configuration automation.
- Strong coding skills in Python, including PySpark, and knowledge of Spark.
- Experience with ML tools like MLFlow and TensorFlow for model deployment.
- Ability to implement observability with various tools like Grafana or Splunk.
- Comfortable working in hybrid environments and integrating with cloud services.
Benefits
- Flexible collaboration model based on a B2B contract.
- Opportunity to work on diverse projects.
Tech Stack
AnsibleApache AirflowApache HadoopApache SparkBashGoogle BigQueryGoogle Cloud PlatformGrafanaGroovyJenkinsMLflowPythonSplunkTensorFlow