AI Engineer (Europe)

What will you do?

• Own the architecture and delivery of production-grade LLM systems and classical ML solutions.

• Design, evaluate, and optimize RAG pipelines (retrieval strategy, chunking, indexing, monitoring).

• Build scalable, production-grade LLM services and agentic workflows, alongside traditional ML systems where appropriate.

• Define architecture trade-offs (LLM vs traditional ML, fine-tuning vs RAG, hosted vs self-managed models), with a strong focus on system-level optimization (latency, cost, scalability, reliability).

• Architect and optimize distributed GenAI and ML workloads on Databricks (Spark, MLflow), leveraging deep understanding of the platform ecosystem.

• Implement evaluation frameworks to measure quality, hallucination, and performance.

• Productionize systems with proper CI/CD, monitoring, rollback, and versioning.