About this role
Summary: Working student role focused on developing algorithms for supply chain optimization, integrating AI-enhanced techniques, and prototyping GPU-accelerated solvers. The position involves mathematical programming, machine learning, and algorithm design within a product-oriented team.
Job Description
What you bring (please specify briefly but as detailed as possible)
- Currently enrolled in Computer Science, Mathematics, Physics, or Operations Research
- Strong programming skills in Python and working knowledge of at least one optimization framework (Gurobi, CPLEX, Xpress, or OR-Tools) — required
- Solid foundations in at least one of: mathematical optimization (LP/MIP, heuristics, metaheuristics), machine learning, or algorithm design
- Ability to design and run reproducible experiments, analyse results rigorously, and document findings clearly
- Interest in applied, enterprise-scale problems — not purely academic settings
- Nice to have: experience with GPU programming (CUDA, cuOpt), ML frameworks (PyTorch, scikit-learn), C++, or operations research decomposition techniques.
What you'll build
You will work on the algorithmic core of the SCM Optimization Service — the mathematical engine behind SAP's supply chain planning. The focus is on three areas:
Classical Optimization. You will develop and improve algorithms for core supply chain and logistics problems. The work covers mathematical programming (MIP), heuristics, and metaheuristics, applied to real-world planning scenarios at enterprise scale.
AI-Enhanced Optimization. You will develop and evaluate machine learning techniques that augment classical optimization: learned heuristics and prediction models for planning parameters. The goal is to improve planning quality and responsiveness beyond what classical solvers alone can achieve.
GPU-Accelerated Solvers. The unit is evaluating GPU architectures for large-scale combinatorial optimization. You will prototype and benchmark solver approaches on GPU hardware, assess which problem classes benefit from massive parallelism (e.g. large-scale supply planning, production scheduling), and contribute to the unit's evaluation of various frameworks.
Where you belong
You will join a technically focused team that develops the optimization capabilities for SAP's supply chain applications. The work is research-adjacent but product-oriented: your findings feed directly into the unit's algorithm portfolio, deployed across SAP Integrated Business Planning, SAP Transportation Management, and SAP Logistics Management.
The team operates at the intersection of mathematical optimization, AI, and quantum computing. Work location is Walldorf, 20 hours per week with flexible scheduling.
*Your set of application documents should contain a cover letter, a resume in table form, school leaving certificates, certificate of enrollment, current university transcript of records, copies of any academic degrees already earned, and if available, references from former employers (including internships). Please also describe your experience and skills in foreign languages and computer programs / programming languages.*
*This is a SAP global, strategic, paid working student position that provides students with opportunities to find purpose in their careers.*
*#Workingstudent #Werkstudent #Germany #Deutschland #Student #LIHybrid #SAPGermanStudentsCareers #SAPNextGen #Optimization #MachineLearning #GPU #SupplyChain #Algorithm #OperationsResearch*
Additional Information
About SAP
With a global network of customers, partners, employees, and thought leaders, SAP helps the world run better and improves people’s lives.
As a leader in enterprise applications and business AI, SAP stands at the nexus of business and technology. For over 50 years, organizations have trusted SAP to bring out their best by uniting business-critical operations spanning finance, procurement, HR, supply chain, and customer experience.
We win with inclusion
SAP’s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone – regardless of background – feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world.
SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: Careers@sap.com.
For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training.
Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements.
AI Usage in the Recruitment Process
For information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.
Please note that any violation of these guidelines may result in disqualification from the hiring process.