At Haldorix, we transform operational challenges into scalable business opportunities through technology. As a Full‑Stack Python/DevOps Engineer, you will play a pivotal role in our venture pipeline, ensuring that data capture, processing, and deployment are seamless and reliable. Your responsibilities include:

• Data Quality & Automation: Design and maintain automated pipelines to guarantee 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 with Flask, ensuring 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.

You will work in a hybrid environment, balancing on‑site collaboration with remote flexibility. The role requires 2+ years of full‑stack experience, strong command of Python (automation, scripting, backend), and proficiency with Docker, Docker Compose, Kubernetes (Helm), CI/CD pipelines, and RESTful API development (Flask or FastAPI). Knowledge of OpenCV, scikit‑image, and image processing is a plus, as is experience with industrial or computer vision systems, data labeling pipelines, MLOps workflows, edge computing, streaming architectures, and observability tools such as Grafana and Prometheus. Experience in startup environments is highly valued.

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 contributing directly to tangible products delivered in record time. The recruitment process involves a Jobzyn AI interview, a technical interview with the Lead Developer or Technical Architect, a practical test based on a real‑world use case, and a final interview with the team and partners.