Senior DevOps Engineer
Generix Group2 months ago
Cluj-Napoca, RomaniaSenior
Responsibilities
- Design, build, and maintain CI/CD pipelines for software applications, ETL/ELT data transformations, and machine learning models.
- Implement and manage Infrastructure as Code using Terraform across cloud and on-premise environments.
- Develop automated data quality checks, data pipeline monitoring, and alerting within DataOps workflows.
- Establish MLOps workflows for experiment tracking, model versioning, automated retraining, and model performance monitoring, including drift and bias detection.
- Implement monitoring, logging, and alerting across applications, data flows, ML models, and operational pipelines.
- Collaborate with software developers, data engineers, data scientists, and analysts to provide operational support and tooling.
- Promote security, reliability, performance, and operational best practices across DevOps, DataOps, and MLOps domains.
- Troubleshoot infrastructure, pipeline, and deployment issues and evaluate tools that improve operational efficiency.
Requirements
- Deep expertise in DevOps, DataOps, and MLOps principles, practices, and tooling.
- Mastery of CI/CD pipeline design for code, data, and machine learning artifacts.
- Strong proficiency in Azure cloud infrastructure management and automation; AWS experience is a plus.
- Expertise with Docker and Kubernetes.
- Strong scripting and automation skills in Python, Bash, or similar languages.
- Experience with monitoring, logging, and observability tools such as Prometheus, Grafana, ELK Stack, and Datadog.
- Understanding of data engineering concepts and data pipeline orchestration tools such as Airflow.
- Familiarity with ML lifecycle management and platforms such as MLflow, Kubeflow, SageMaker, and Vertex AI.
- Proven experience with CI/CD tools including Jenkins, GitLab CI, or ArgoCD and IaC tools such as Terraform.
- Bachelor’s or master’s degree in computer science, engineering, or a related field.
- At least 5 years of experience in technical operations, including hands-on implementation of DataOps and MLOps practices.
- Fluent English or French.
Benefits
- Access to modern tools and technologies.
- Opportunities to make a meaningful impact on enterprise product quality.
- Career growth and development opportunities.
- Soft-skills and technical training, workshops, conferences, and attendance at similar events.
Tech Stack
Categories