Lead DevOps/MLOps Engineer
We are seeking a driven and highly skilled Lead DevOps/MLOps Engineer to assess client infrastructure to enable the deployment of Enterprise Data Platform (EDP) components, aiming to ensure seamless integration and operational efficiency for a leading oil and gas company. The focus is on evaluating existing systems and preparing them for a scalable data platform rollout.
Responsibilities
- Conduct comprehensive assessments of client infrastructure for EDP rollout feasibility
- Identify and document infrastructure gaps and recommend remediation actions
- Collaborate with data engineering and DevOps teams to align deployment strategies
- Develop and maintain deployment automation scripts and tools
- Coordinate with third-party vendors to ensure compatibility and support
- Monitor infrastructure performance and provide feedback for optimization
- Support continuous improvement of deployment processes and infrastructure standards
- Deploy platform and application workloads on Kubernetes
Requirements
- 5+ years of experience in DevOps practices tailored to data engineering environments
- Expertise in infrastructure assessment and readiness evaluation for data platform deployments
- Knowledge of EDP components and their deployment requirements
- Ability to analyze complex client environments and identify potential integration challenges
- Experience collaborating within cross-functional teams and coordinating with external vendors
- Proficiency in Docker, Kubernetes, and Linux
- Skills in CI/CD, Argo, and Python
- Understanding of machine learning and agentic AI applications, and what it takes to deploy and run them reliably in production
- English proficiency at B2 level or higher
Nice to have
- Background in MLflow and Airflow
- Knowledge of automated retraining tools
- Exposure to data quality and monitoring tools
