Software-Design and Development
At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging – but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.
Responsibilities
- Own pre-training, evaluation, and meta-data including proprietary, open-source, and synthetic datasets. Develop and execute vision.
- Lead data extraction, curation, and quality analysis to produce high-impact training signals. Set technical priorities and define work packages across teams to ensure high-quality outcomes.
- Work closely with science leads to define data requirements and co-design the datasets necessary to push model capabilities. Build strong alliances with internal data and technology providers.
- Explore and analyze datasets to identify patterns, edge cases, and quality issues that inform model development.
- Influence data architecture decisions to ensure seamless data access for both model training and production environments.
Requirements
- PhD or Masters degree in Computer Science, AI, or a relevant field, followed by 7+ years of professional experience in high-scale data environments.
- Proven track record of leading large-scale, end-to-end technical projects, ideally with data and machine learning deliverables.
- Profound understanding of SAP's relational business data, including key business objects and underlying table structures. Sophisticated understanding of the complex business logic and relational schemas inherent in the enterprise landscape.
- Extensive experience with high-performance databases (SQL) and SAP's data stack (e.g. BDC, HANA & BTP) as well as with the development of cloud-native pipelines. Strong Python skills and ideally exposure to Knowledge Graphs (incl technologies like RDL).
- Solid ML knowledge with practical experience in solving real-world problems with AI - ideally in the tabular domain.
- Ability to build partnerships with internal technology providers and lead cross-team technical initiatives and task prioritization.
Benefits
- Competitive compensation and benefits package
- Opportunities for career growth and development
- Collaborative and inclusive work environment
- Flexible working arrangements
- Health and wellness programs