Senior AI Machine Learning Engineer

Lead the development of scalable graph-based and transformer-based modeling systems at SAP, building the next generation of relational foundation models for structured data. This role sits at the intersection of research and systems engineering, requiring ownership of key architecture decisions and mentoring of engineers. You will design high-performance ML pipelines and operate distributed training systems in production.

• Architect and drive scalable development of foundation models for relational and graph data. Design high-performance data pipelines for large-scale graph, relational, and tabular datasets. Establish best practices for experimentation, reproducibility, evaluation, and deployment. Build and operate distributed training and inference pipelines. Mentor ML engineers and collaborate with research and product stakeholders.

• PhD or MS in CS, ML, or related field with 5+ years experience. Strong hands-on with PyTorch, PyTorch Geometric or DGL. Experience designing distributed systems and scalable ML infrastructure. Advanced Python and software engineering fundamentals. Demonstrated ownership of complex ML projects from design to production. Experience scaling ML in cloud environments like Azure or AWS.

• Experience building foundation models for structured or graph data. Familiarity with transformer architectures for graph/tabular domains. Experience with distributed training frameworks (FSDP, DeepSpeed, Ray). Deep expertise in graph representation learning or large-scale training systems. Publications in top ML venues (NeurIPS, ICML, ICLR, KDD).