About the Job: Yassir is the leading super app in the Maghreb region, revolutionizing the way daily services are provided. Operating in 45 cities across Algeria, Morocco, and Tunisia, Yassir has recently expanded into France, Canada, and Sub-Saharan Africa, backed by approximately $200M in funding from various VCs globally. We offer on-demand services such as ride-hailing and last-mile delivery, and we are now introducing financial services to facilitate digital payments, savings, and loans for our users. Our mission is to usher the continent into a digital economy era, creating a marketplace that fulfills people's needs while promoting social values.
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About the Role: Yassir is seeking a highly skilled and motivated MLOps Engineer to join our Artificial Intelligence (AI) team. This role involves driving our ML Operations in application deployment and infrastructure development, enabling the training, deployment, experimentation, monitoring, and management of our ML applications at scale and speed. As an MLOps Engineer, you will have a pivotal role in enhancing Yassir's products and operations through the use of modern technologies, tackling some of our most critical challenges.
Key Responsibilities: - 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 cloud platforms (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.
Key Requirements: - 5+ years of experience in MLOps, DevOps for AI/ML, or Machine Learning Engineering. - Clear knowledge of the end-to-end ML lifecycle. - Strong programming skills in Python and familiarity with common ML libraries (e.g., scikit-learn, TensorFlow, PyTorch). - Knowledge and experience with Infrastructure-as-Code (IaC), preferably Terraform. - Proficiency in containerization (Docker). - Experience with cloud platforms (GCP preferred, or AWS/Azure) and their ML-related services (e.g., 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.
Language Requirements: Not specified in the posting. At Yassir, we embrace diversity and value an inclusive culture. If you're ready to bring your unique perspective and experiences to our team, we'd love to hear from you. Join us in creating a better tomorrow together!
