SENIOR MLOPS ENGINEER AT YASSIR NIGERIA

About Company:

Yassir is the leading super App in the Maghreb region set to changing the way daily services are provided. It currently operates in 45 cities across Algeria, Morocco and Tunisia with recent expansions into France, Canada and Sub-Saharan Africa. It is backed (~$200M in funding) by VCs from Silicon Valley, Europe and other parts of the world.

Job Description:

• Deploy and monitor AI / ML models in production using CI/CD and MLOps best practices (e.g., retraining pipelines, model versioning, rollback strategies)
• Design and maintain scalable and secure MLOps infrastructure, leveraging our cloud platform (GCP), containerization (Docker, Kubernetes), and orchestration tools (Airflow, Kubeflow, Vertex AI, or similar)
• Collaborate closely with Data Scientists, ML Engineers, and DevOps to build end-to-end ML systems - from experimentation to monitoring
• Implement automated testing, performance monitoring, alerting and drift detection pipelines for deployed models
• Ensure governance, traceability, and compliance of ML assets (e.g., model registry, audit trails, data lineage)
• Support AI governance and contribute to enforcing policies and controls across model lifecycle stages
• Identify bottlenecks, propose optimizations, and drive platform-wide observability and scalability efforts
• Contribute to documentation, onboarding materials, and internal tooling for self-service ML infrastructure

Requirements:

• Knowledge and experience with Infrastructure-as-Code (IaC), and ideally Terraform
• Proficiency in containerization (Docker)
• Experience with cloud platforms (GCP much preferred, or AWS/Azure) and their ML-related services (e.g. for GCP: Vertex AI, Cloud Run, Kubernetes Engine, BigQuery)
• Experience with CI/CD tools (e.g. GitHub Actions), Good understanding of data pipelines, feature stores, monitoring and alerting tools
• Experience with SQL
• Experience with Prometheus, Grafana, or SonarQube.

Qualifications and Skills:

• 5+ years of experience in MLOps, DevOps for AI/ML, Machine Learning Engineering
• Clear knowledge of the end-to-end ML LifecycleStrong programming skills in Python, and familiarity with common ML libraries (e.g. scikit-learn, TensorFlow, PyTorch)

Salary

Application Closing Date: Not specified

Application Instructions:

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