GenAI/ML Engineer
Core
Design and build end-to-end machine learning and GenAI solutions for financial services clients, managing the full lifecycle from data pipelines to production deployment.
Role type
Senior GenAI/ML Engineer
Builds
End-to-end data pipelines, feature engineering workflows, GenAI-powered agentic workflows, RAG systems, and LLM-based automation.
Domain
Financial services
Deliverable
production ML models
Required skills
Python, Spark, CI/CD, Kubernetes, Airflow, feature engineering at scale, statistical modeling, model explainability (Shapley Values), tree-based methods, neural networks, hyperparameter optimization, LLM integration, prompt engineering, RAG architectures, agentic workflows
Preferred skills
Fluent German, strong client-facing communication skills
Technologies
Python, Spark, Kubernetes, Airflow
Responsibilities
Design and build end-to-end data pipelines and feature engineering workflows on large-scale transactional data; Train, calibrate, and validate ML models including threshold analysis and production-grade explainability; Develop GenAI-powered solutions such as agentic workflows, RAG systems, and LLM-based automation; Deploy and monitor models in production with drift detection and performance tracking; Work directly with client stakeholders delivering documentation and knowledge transfer
