Teams at Faktion BV

Design, train, evaluate, deploy, and maintain computer vision and deep learning systems for industrial applications. Build Azure Machine Learning training and inference pipelines, process large and multispectral image datasets, analyze model errors, and optimize real-time inference for production hardware. Contribute to shared MLOps platforms, tooling, CI/CD, testing, monitoring, and deployment infrastructure while collaborating with engineering and customer teams. Responsibilities also include dataset curation, annotation strategy, production debugging, technical reviews, and mentoring.

Deploys, scales, secures, and maintains cloud platforms and services. Responsibilities include building Azure DevOps CI/CD pipelines, managing Azure infrastructure with Terraform or Bicep, containerizing Node.js and ML services using Docker and Kubernetes, monitoring performance, implementing observability, optimizing cloud costs, and planning networking and disaster recovery.

Lead design, development, and deployment of scalable Java backend systems using the Spring ecosystem. Collaborate with AI/ML teams and stakeholders, define architecture and testing standards, run code reviews, mentor junior engineers, manage production deployments, optimize performance, and promote best practices across projects.