You design, implement, test, deploy, and maintain data- and model-centric systems that deliver production-grade ML functionality. Typical tasks span:

Machine Learning Engineering

• Build end-to-end ML training pipelines (ingestion, validation, transformation, training, evaluation)
• Deploy, optimize and package models for inference
• Support the platform team to serve models in cloud
• Support the ai runtime team to serve models on edge/sorters
• Participate in data and model centric research and innovation

Data Management

• Build, integrate and maintain secure data platforms (e.g., SQL/NoSQL warehouses, object storage, feature stores)
• Ensure data security, privacy, and compliance

Service & ML Tooling

• Design and implement REST APIs to expose ML services and data platform functionality
• Develop and maintain internal tools and web-based UIs that support ML wor...