ml engineer GenAI infrastructure

Sunday Natural produces natural, high-quality health and wellness products, including essential oils, vitamins, and nutrients. The company conducts its own research and development in Berlin and collaborates with research institutes, scientists, therapists, farmers, and professional associations.

• Design, build, and maintain modular, reusable ML pipelines in Vertex AI Pipelines covering training, evaluation, deployment, monitoring, and retraining;
• Develop GenAI capabilities including embeddings, retrieval pipelines, vector databases, and RAG frameworks for chatbots, personalisation, and semantic search;
• Build and manage feature stores and reusable datasets in collaboration with Data Engineers and Analysts;
• Productionise workflows with Prefect orchestration and CI/CD pipelines in Bitbucket;
• Implement continuous evaluation, drift detection, performance monitoring, rollback strategies, and retraining triggers for deployed models;
• Embed GDPR compliance, RBAC, anonymisation, explainability, fairness, and auditability into every model and pipeline;
• Document lineage of features, models, and inference workflows, and partner with the Data Governance Lead on ethical AI frameworks;
• Translate technical capabilities into business-friendly outcomes, communicating trade-offs across accuracy, latency, and cost to non-technical stakeholders;
• Mentor Data Engineers in ML Ops and GenAI techniques, and contribute to internal AI/ML guilds and best practices.

• At least 5 years of experience in Data Engineering or ML Ops, including at least 3 years focused on productionising ML pipelines;
• Degree in Computer Science, Data Science, Engineering, or a related field;
• Expert proficiency in Python and ML/DL libraries such as scikit-learn, TensorFlow, PyTorch, Hugging Face, and LangChain;
• Strong knowledge of BigQuery, db, and SQL for feature and data preparation;
• Hands-on experience with Vertex AI for pipeline orchestration, deployment, and monitoring, or AWS/GCP equivalents;
• Experience with Prefect orchestration and CI/CD pipelines in Bitbucket;
• Familiarity with ML Ops frameworks such as MLflow or TFX, and containerisation with Docker and Kubernetes;
• Experience with vector databases such as Pinecone, FAISS, or Milvus;
• Proven delivery of ML or GenAI use cases in production with measurable business impact;
• Strong stakeholder communication and ability to translate AI/ML into measurable business outcomes;
• Systems thinking with strong ethical grounding in responsible AI, balancing innovation with operational reliability and cost control;
• Nice to have: PhD.

• 28 Days of paid time off per year plus up to 5 days off between Christmas and New Year;
• Discount on all company products;
• Urban Sports Club membership;
• Choice of Swapfiets bike rental or a subsidy for the Deutschlandticket;
• Up to two weeks per year working from abroad;
• Discounts of up to more than 50 percent on selected brands;
• Real ownership and room for new initiatives;
• Inviting office spaces with organic teas and superfoods;
• Regular tea and office parties, Christmas and summer feasts, and influencer events.