Responsibilities
- Architect and drive scalable foundation-model development for relational and graph data.
- Design high-performance pipelines for large-scale graph, relational, and tabular datasets.
- Develop and optimize Graph Neural Networks, Graph Transformers, Relational Transformers, and structured-data pretraining strategies.
- Build and operate distributed ML training and inference pipelines.
- Optimize GPU/CPU utilization, memory footprint, training throughput, and inference latency.
- Define technical roadmaps for ML infrastructure and modeling frameworks.
- Translate research innovations into production-ready systems and establish practices for experimentation, reproducibility, evaluation, and deployment.
- Partner with platform teams on production deployment, monitoring, and reliability.
- Mentor ML engineers and applied scientists and provide technical guidance and reviews.
- Collaborate with research, data, and product stakeholders to deliver ML systems and business impact.
Requirements
- PhD or MS in Computer Science, Machine Learning, Applied Mathematics, Physics, or a related field, with substantial applied experience.
- At least 5 years of experience building and delivering ML systems end to end.
- Strong hands-on experience with PyTorch and PyTorch Geometric and/or Deep Graph Library.
- Experience designing and developing distributed systems and scalable ML infrastructure.
- Advanced Python proficiency and strong software engineering fundamentals.
- Demonstrated ownership of complex ML projects from design through production.
- Experience scaling ML systems in cloud environments such as Azure or AWS.
- Preferred: experience building foundation models for structured, relational, or graph data.
- Preferred: familiarity with graph- and tabular-domain transformer architectures.
- Preferred: experience with FSDP, DeepSpeed, or Ray for distributed training.
- Preferred: expertise in graph representation learning, structured or relational modeling, and large-scale training systems.
- Preferred: publications in venues such as NeurIPS, ICML, ICLR, or KDD.
Benefits
- SAP offers health and well-being support, flexible working models, inclusion programs, and personal development opportunities.
- The role is regular full-time with expected travel of 0–10%.
- The posting indicates a hybrid work arrangement and SAP North America benefits eligibility.
Categories
About SAP
SAP is a global leader in enterprise applications and business AI. We help organizations run mission-critical operations across finance, procurement, supply chain, human resources, and customer experience -and move from systems that record work to systems that can help execute it. The Autonomous Enterprise brings together enterprise applications, trusted business data, and AI assistants and agents that can reason, recommend, and act within business processes -with governance, accuracy, and compliance built in. • Joule: the new engagement layer, bringing together data, workflows, and agents across SAP systems and beyond. • SAP Autonomous Suite: based on AI assistants and agents executing work across all domains. • Industry AI applications with built-in vertical processes, knowledge, data models, and regulatory logic. • SAP Business AI platform as the foundation that combines context, unified business data, and purpose-built models with enterprise governance. • Cloud Transformation: RISE with SAP and SAP GROW help organizations modernize their ERP landscape, move to the cloud, and adopt AI based on their business needs and starting point. Include SAP S/4HANA Cloud, acceleration services, and tools. Our Partners amplify SAP's value through solution innovations, deep product expertise, world-class services, and more. We’re committed to fostering meaningful, respectful conversations. To maintain a positive environment, we moderate comments that: Target individuals, including employees, customers, or partners. Contain discriminatory, harassing, or threatening content. Share personal information without consent. Promote misinformation, spam, or third-party links. We support open dialogue and constructive feedback but will remove content that violates these guidelines without notice. Thank you for contributing to a respectful community. For questions about moderation, please DM us or contact brandsocial@sap.com. SAP privacy statement for followers: www.sap.com/sps