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About the Role

We are seeking an experienced AI/ML Engineer to own the machine learning and GenAI infrastructure, driving advanced analytics and AI use cases. You will design, build, and maintain end-to-end ML pipelines in Vertex AI, ensuring seamless transition from prototype to production with monitoring, cost efficiency, and compliance. This role pioneers GenAI enablement, including RAG, embeddings, and AI-driven applications, embedding governance, reproducibility, and scalability from the start. You will act as a liaison between technical teams and business stakeholders to ensure AI/ML initiatives deliver measurable business impact.

Responsibilities

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.

Requirements

5 to 7 years of experience in Data Engineering or ML Ops, with at least 3 years focused on productionising ML pipelines.
Strong stakeholder communication and the ability to translate AI/ML into measurable business outcomes.
Systems thinker with strong ethical grounding in responsible AI; balances innovation with operational reliability and cost control.

Skills

Python
ML/DL libraries (scikit-learn, TensorFlow, PyTorch, Hugging Face, LangChain)
BigQuery
dbt
SQL
Vertex AI
Prefect orchestration
CI/CD pipelines in Bitbucket
MLflow
TFX
Docker
Kubernetes
Vector databases (Pinecone, FAISS, Milvus)

Location

Berlin

Work Type

Hybrid
Full-time

Experience Level

Mid-level
Senior

Education Level

Degree in Computer Science, Data Science, Engineering, or a related field
PhD a plus

Benefits

28 days of paid time off per year plus up to 5 days off between Christmas and New Year
Urban Sports Club membership
Swapfiets bike rental or a subsidy for the Deutschlandticket
Discounts on various brands (Flaconi, Bosch, Apple, Expedia)
Real ownership and room for new initiatives
Inviting office spaces with organic teas and superfoods
Regular parties and feasts
An appealing discount on all of our products

About the Company

Sunday Natural emerged from a long-standing passion and research in the fields of health, healing, and personal growth.
We aim to produce products that are as natural as possible, absolutely pure, free from any additives, and of the highest quality.
In a strategic partnership with CVC, Sunday Natural is now one of Germany's most renowned quality manufacturers, with its own research and development department in Berlin.
For the continuous improvement of our products, we collaborate with selected research institutes, scientists, therapists, farmers, and professional associations.
We take our ecological responsibility very seriously: the majority of our product range is vegan.
We take an innovative approach to packaging: most of our products are packaged in glass, making them almost entirely recyclable.
Our diverse team in Berlin consists of over 350 employees from more than 45 nationalities and continues to grow – but at a sustainable pace.
Our goal is to foster a collaborative, supportive, and inclusive work environment with a diverse group of motivated, talented, and visionary team members.

Equal Opportunity

We highly value equality of opportunity and inclusivity, and we would like to particularly encourage women and candidates from under-represented backgrounds to apply, even if you don’t match with 100% of the requirements.