Haldorix, a startup studio based in Casablanca, is on a mission to transform operational challenges into scalable business solutions through technology. We identify recurring problems in manufacturing, retail, and logistics, and turn them into ventures that deliver measurable value. Our current ventures include DeVisu, a computer‑vision solution for operational optimization, and Nitra3AI, a generative AI platform for industrial performance enhancement.

We are looking for a Full‑Stack Python/DevOps Engineer who will play a pivotal role in our AI and automation initiatives. Your responsibilities will include:

• Data Quality & Automation: Design and maintain automated pipelines to ensure high‑quality video capture, data integrity, and continuous dataset backups.
• Image Processing & Pre‑Labelling: Implement pre‑labelling and automated clip processing pipelines using Python, OpenCV, and scikit‑image.
• Backend Engineering: Develop and maintain the HD Zoom Manager service using Flask, ensuring reliable, low‑latency video recording and retrieval.
• Containerization & Deployment: Package applications with Docker and Helm, and oversee seamless deployment across Kubernetes clusters.
• System Integration: Collaborate with other engineers to ensure all components from data capture to visualization work together in real time.
• CI/CD & Reliability: Apply DevOps best practices to automate testing, deployment, and monitoring, ensuring system reliability throughout the sprint.
• Documentation & Handover: Deliver clear deployment manifests and technical documentation to support long‑term scalability and maintainability.

We value a candidate with:

• 2+ years of full‑stack engineering experience with strong DevOps fundamentals.
• Proficiency in Python (automation, scripting, backend).
• Experience with Docker, Docker Compose, Kubernetes (Helm).
• Hands‑on with CI/CD pipelines and deployment automation.
• RESTful API development using Flask or FastAPI.
• Solid foundation in image processing (OpenCV, scikit‑image).
• Familiarity with data labeling pipelines or MLOps workflows.
• Understanding of edge computing and streaming architectures.
• Exposure to Grafana, Prometheus, or observability tools.
• Experience in startup environments.

Benefits include working on cutting‑edge industrial AI projects from concept to production in just 10 days, collaborating with experts in AI, vision systems, and automation, and being part of a high‑energy, collaborative engineering team. The role is a full‑time CDI with hybrid working arrangements, offering flexibility and the opportunity to grow within a fast‑paced startup studio.

Recruitment Process:

1. Jobzyn AI interview (25–45 min).
2. Technical interview (1h) with the Lead Developer or Technical Architect.
3. Practical test (2–3h) based on a real‑world use‑case.
4. Final interview with the team and partners.