(Senior) AI/ML Engineer (all genders)

About This Opportunity

We are representing a confidential health and wellness organization in Berlin that is building enterprise-grade AI and machine learning capabilities. Our talent team is seeking an experienced AI/ML Engineer to join a Central Data Platform team and take ownership of the machine learning and GenAI infrastructure that powers advanced analytics and AI use cases across the business.

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 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. 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.

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, personalization, and semantic search
• Build and manage feature stores and reusable datasets in collaboration with Data Engineers and Analysts
• Productionize 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, anonymization, explainability, fairness, and auditability into every model and pipeline
• Document lineage of features, models, and inference workflows, and partner with Data Governance teams 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 MLOps and GenAI techniques, and contribute to internal AI/ML guilds and best practices

What We're Looking For

• At least 5 years of experience in Data Engineering or MLOps, with at least 3 years focused on productionizing 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 experience with BigQuery 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 MLOps frameworks such as MLflow or TFX, and containerization 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

How We Work With You

When you apply through Get A Job.ai, our recruiting team will review your profile and conduct an initial screening. If there's a strong match, we will submit your candidacy to our client for consideration. Please apply only through our platform and do not contact the employer directly, as all applications are managed exclusively through Get A Job.ai.

Pay

Compensation details will be discussed during the screening process based on experience and qualifications.

Equal Employment Opportunity: Get A Job.ai is committed to inclusive hiring practices. We encourage applications from candidates of all backgrounds and experiences.