At enliteAI, we’re proud to offer innovative AI-based software applications that meet the needs and wants of our customers. Detekt, one of our products, is a modern Geospatial Data Platform for object and damage detection in Mobile Mapping data which had its product launch in April 2022.

We are seeking an experienced and enthusiastic MLOps Engineer to work as part of our product development team for Detekt, a Geospatial Data Platform applying large scale computer vision to Mobile Mapping data.

• Collaborate with our machine learning engineers and data engineers to publish our models into processing pipelines and deploy to productive environments.
• Design and manage our GPU & CPU server infrastructure, from on-prem Kubernetes clusters to cloud deployments.
• Manage and orchestrate the data pipelines and data storage systems and associated synchronization processes for model training and execution.
• Own our CI/CD pipelines (based on Gitlab)
• Establish monitoring of model, pipeline and infrastructure health. Set up logging to capture relevant information for debugging and auditing.
• Enforce security best practices to safeguard both the models and the data they process.
• Create and maintain comprehensive documentation of the infrastructure, deployments, configuration and system architecture.

• 3+ years of work experience in data-driven environments
• Passionate about everything related to AI, Machine Learning and Computer Vision
• Experience with Kubernetes and Docker (Helm, Terraform, Amazon Kubernetes Service)
• Familiarity with cloud environments (AWS, Gcloud, Azure)
• Python programming skills, emphasis on backend related technologies (e.g. Flask, Postgres, SQLalchemy)
• Used to mature workflows in software development (Git, issue management, documentation, unit testing, CI/CD)
• Data engineering knowledge (SQL databases, distributed systems)
• Fluent in English both spoken and in written language.
• Valid work permit for Austria

• International product and innovation-driven team with rich expertise in Computer Vision and Reinforcement Learning as well as distributed training, data engineering, ML ops and cloud architectures
• Working with the latest technologies at the interface between research and industry (enliteAI is an ELISE EU research network Organizing Node)
• Personal growth: Receive continuous training and education opportunities. Budget and time allotment for the pursuit of individual R&D projects, training or conference participations
• Flexible work models: Remote work, an office in Vienna's 1st district and minimal core hours