Data Business Analyst & Adoption Lead
HybridCasablanca, Casablanca-Settat, Morocco or Casablanca, North Carolina, United States
Job Summary
Design, deploy, and operate AI platforms ensuring reliability, scalability, and security in production environments. Collaborate with data scientists, engineers, and infrastructure teams to industrialize AI use cases on cloud and hybrid platforms. Implement and maintain MLOps tooling and pipelines for model training, evaluation, and monitoring. Automate and standardize platform services using templates, CI/CD, and infrastructure as code to accelerate delivery while maintaining quality. Participate in incident analysis and continuous improvement of the AI platform to foster a strong reliability and performance culture. Contribute to the rollout of new features like GPU-based training environments and model registries, and assist in migration projects to new cloud services or AI frameworks. Join an international team working on visible, impactful projects across multiple countries and industries.
Required Qualifications
- 3 to 5 years of professional experience in a relevant technical role (for example: platform engineer, DevOps engineer, data/ML engineer, software engineer)
- at least a Bachelor's or Master's degree (or equivalent) in computer science, engineering or a related field
- Good knowledge of cloud environments (AWS, Azure or GCP) and their managed services for data and AI
- Solid experience with containers and orchestration (Docker, Kubernetes) in production contexts
- Hands-on experience with CI/CD and DevOps practices (Git, pipelines, infrastructure as code such as Terraform/Ansible, monitoring/logging tools)
- Familiarity with AI and ML concepts and tools (for example Python-based ML stacks, model serving frameworks, MLOps tools)
- Understanding of security, reliability and performance considerations for production platforms
Desired Qualifications
- a strong motivation to grow further in this area
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