Principal ML Engineer (Agentic AI)-Vendor Data Team

Requirements:

• Strong experience designing and scaling production-grade ML systems and data platforms, including large-scale deployments
• Deep expertise in data engineering and ML pipelines, including feature/data pipelines, RAG systems, and embedding workflows
• Proven experience building and maintaining reliable data infrastructure with strong guarantees around data quality and freshness
• Strong engineering skills in Python and SQL, with experience in Docker, Kubernetes, and cloud environments
• Experience with Infrastructure as Code (e.g., Terraform or similar) and building reproducible, scalable systems
• Hands-on experience integrating ML systems with real-world APIs and services, and operating them in production with monitoring and observability

Nice to have:

• Experience with LLMs, agent architectures, or orchestration frameworks (LangGraph, AutoGen, CrewAI, etc.)
• Familiarity with synthetic data generation, evaluation systems, or AI feedback loops
• Experience with agent or ML observability tools such as Langfuse or LangSmith
• Experience with model serving, routing, or inference optimization
• Experience with open-source models (e.g., LLaMA, Mistral, Mixtral) or custom inference stacks
• Knowledge of system reliability, failure handling, and safety patterns in AI systems

What you'll be doing:

• Design and own end-to-end ML and data systems — from ingestion and transformation to model integration and production deployment
• Architect and maintain scalable data pipelines for RAG, embeddings, and real-time/near-real-time data processing
• Build and operate production-grade ML services and APIs, ensuring reliability, scalability, and performance
• Define standards for infrastructure, deployment, and system reliability, including Infrastructure as Code, containerization, and orchestration
• Integrate ML systems with external APIs, tools, and operational platforms, enabling real-world actions and automation
• Establish monitoring, evaluation, and observability frameworks across data, models, and systems, while mentoring engineers and setting technical direction.

Perks and benefits:

• Make the most of our hybrid working model and join the team for face-to-face connection and collaboration in our beautiful Berlin campus 2 days a week
• We offer 27 days holiday with an extra day on 2nd and 3rd year of service
• We will support you in developing yourself and your career growth opportunities: 1.000 € Educational Budget, Language Courses, Parental Support and access to the Udemy Business platform to explore a variety of online courses.
• Get moving and release those wonderful, mind-boosting endorphins: Health Checkups, Meditation, Gym & Bicycle Subsidy
• Cash. Dough. Cheddar. Whatever you call it, we’ll help you with it: Employee Share Purchase Plan, Sabbatical Bank, Public Transportation Ticket Discount, Life & Accident Insurance, Corporate Pension Plan
• The power of getting together over some food is unrivaled. Here are a few ways to help you do that. All the yum: Digital Meal Vouchers, Food Vouchers, Corporate Discounts. Courses.