Machine Learning Operations Engineer
About the role
CRDB Bank Plc seeks a Machine Learning Operations Engineer in the Data Management Office at its Tanzania Head Office. The role operates the shared technology and release processes that keep AI models and services reliable, secure and supportable, and automates controlled deployment, monitoring and recovery. Responsibilities: - Operate approved AI platform environments and document service ownership, dependencies, capacity and support arrangements with ICT. - Automate build, test and release workflows, and keep development, testing and production environments separate. - Manage model registries, approved deployment artefacts and environment configuration with versioned release and approval records. - Deploy model packages only after required validation, governance and change-management conditions are met. - Implement release checks, controlled rollout, rollback and recovery procedures. - Configure platform access, service identities and secrets under approved policies with ICT and Cybersecurity. - Maintain monitoring and alerting for service availability, latency, failures and resource consumption. - Manage approved AI cloud-service usage, quotas and cost allocation. - Support incidents through triage, recovery, root-cause analysis and corrective actions. - Implement and support CI/CD pipelines, automated testing and Infrastructure-as-Code practices for AI solution delivery. How to apply: Search for the vacancy title, register or sign in, and submit your CV and relevant supporting documents before the deadline. Apply online through the CRDB Bank careers portal: https://careers.crdbbank.co.tz/jobs
Key requirements
- Bachelor's degree in Computer Science, Software Engineering, Information Technology, Artificial Intelligence, Machine Learning, Data Engineering, Cloud Computing, or a related field.
- A Master's degree in a related field is an added advantage.
- Minimum of 3 years of experience in DevOps, MLOps, platform engineering, cloud engineering, site reliability engineering or production operations, including ML, AI or data workloads.
- DevOps, cloud, MLOps, container-platform or SRE certifications are an added advantage.
- Skills in Python or shell scripting, Linux, containers, automated delivery pipelines and infrastructure configuration.
- Experience with monitoring, access control, incident response, backup and recovery.
- Knowledge of machine learning lifecycle management, model deployment, model registries, experiment tracking and model monitoring.
- Experience working with Data Scientists, ML Engineers, ICT and Cybersecurity teams on AI and analytics solutions.
- MLOps
- CI/CD
- Python
- Linux