About the RoleWe are seeking a talented data scientist to join our team. As a key member of our group, you will design, implement, and maintain machine learning systems, implement MLOps best practices, and support hybrid cloud deployments.Key ResponsibilitiesDesign, implement, and maintain tools and reusable components that power our machine learning initiatives in the cloud.Scale up training and batch inference with ML frameworks using Vertex AI, and implement real-time inference and GenAI systems.Contribute to internal Python libraries used across various data teams, packaged with pixi, and implement changes to our cookiecutter-based project templates.Implement and champion MLOps principles to ensure seamless integration, deployment, and monitoring of ML models using Gitlab CI for CI/CD and Dagster for workflow orchestration.Define and implement architecture for sending model outputs to various target systems, such as CRM tools or back-end services.Integrate and fine-tune cutting-edge Generative AI models for real-world applications.RequirementsSeveral years of experience in machine learning with end-to-end project ownership and strong Python and software engineering skills.A proven ability to train, evaluate, and deploy ML models across diverse data types and production environments using tools like FastAPI, Docker, Kubernetes & Vertex AI and familiarity with Generative AI technologies, including LLM integration (e.g., LangChain), RAG pipelines, and prompt engineering.A very good understanding of MLOps practices, including CI/CD automation, observability, and monitoring for ML systems.Strong collaboration and system design skills, with the ability to simplify complex architectures and work effectively in agile, cross-functional teams.About UsWe believe in diverse employees and live equal opportunities. We welcome all applications regardless of cultural and social background, age, gender, nationality, religion, disability or sexual orientation. We connect all people.