(Senior) AI/ML Engineer (all genders)
Build and maintain ML pipelines in Vertex AI and pioneer GenAI features like RAG and embeddings to power analytics and AI apps across the company.
- Compensation
- Not disclosed
- Location
- Berlin
- Work setup
- Onsite
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- At least 5 years of experience in Data Engineering or ML Ops, with at least 3 years focused on productionising ML pipelines.
- A degree in Computer Science, Data Science, Engineering, or a related field. PhD a plus.
- Expert proficiency in Python and ML/DL libraries such as scikit-learn, TensorFlow, PyTorch, Hugging Face, and LangChain.
- Strong with 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 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.
Full description
Your role
We are looking for an experienced (Senior) AI/ML Engineer to join our Central Data Platform team and take ownership of the machine learning and GenAI infrastructure that powers advanced analytics and AI use cases across the organization.
In this role, you will design, build, and maintain end to end ML pipelines in Vertex AI, ensuring that models move seamlessly from prototype to production ready, monitored, cost efficient, and compliant pipelines. You will also pioneer GenAI enablement, including retrieval augmented generation, embeddings, and AI driven applications, while embedding governance, reproducibility, and scalability from day one.
This is a pivotal position with high impact on how AI and machine learning capabilities are delivered, scaled, and governed at Sunday Natural. You will act as the bridge between Data Engineers, Senior Data Analysts, Data Scientists, and business stakeholders, ensuring AI/ML work has measurable, repeatable, and strategic business impact.
- 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.
Your profile
- At least 5 years of experience in Data Engineering or ML Ops, with at least 3 years focused on productionising ML pipelines.
- A degree in Computer Science, Data Science, Engineering, or a related field. PhD a plus.
- Expert proficiency in Python and ML/DL libraries such as scikit-learn, TensorFlow, PyTorch, Hugging Face, and LangChain.