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About the Role

We are hiring a Senior Machine Learning Engineer Scientist to lead the development of scalable graph-based and transformer-based modeling systems, along with production-grade ML pipelines. This role sits at the intersection of research and systems engineering and will help shape the next generation of relational foundation model for structured data.

You will own key architecture decisions, mentor engineers and researchers, and build high-performance ML systems that operate reliably at scale.

What You'll Do

Technical Leadership

.  Architect and drive the scalable development of foundation model 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.

Define and execute the technical roadmap for ML infrastructure and modeling frameworks.

Geometric ML Knowledge

Develop and optimize:

      o Graph Neural Networks (GNNs), Graph Transformers, and Relational Transformers

      o Self-supervised, contrastive, and related pretraining strategies for structured data

Translate research innovations into robust, production-ready systems.

Scalable Systems & Infrastructure

Build and operate distributed training and inference pipelines with solid software design & architecture strategy.

Optimize compute efficiency (GPU/CPU utilization), memory footprint, training throughput, and inference latency.

Apply or evaluate techniques such as pruning, quantization, architecture search, and model compilation as needed.

Partner with platform teams to ensure smooth deployment, monitoring, and reliability in production.

Collaboration & Mentorship

Mentor ML engineers and applied scientists; raise the team's technical bar through guidance and review.

Collaborate closely with research, data, and product stakeholders to drive delivery and impact.

Required Qualifications

PhD or MS in Computer Science, Machine Learning, Applied Mathematics, Physics, or a related field, with substantial applied experience.

5+ years building and delivering ML systems end-to-end.

Strong hands-on experience with:

        o PyTorch

        o PyTorch Geometric and/or Deep Graph Library (DGL)

Experience of 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 (e.g., Azure, AWS).

Preferred Qualifications

Experience building foundation models for structured, relational, or graph data.

Familiarity with transformer architectures tailored to graph and tabular domains.

Experience with distributed training frameworks (e.g., FSDP, DeepSpeed, Ray).

Deep expertise in:

         o Graph representation learning

         o Structured / relational modeling

         o Large-scale training systems

Publications in top-tier ML venues (e.g., NeurIPS, ICML, ICLR, KDD).

What We're Looking For

A systems-minded scientist who bridges research depth with engineering rigor.

A strong architectural thinker who can design scalable solutions with long-term maintainability.

A leader who mentors others and elevates engineering and research standards.

Passion for advancing structured-data AI and building platforms that deliver real-world impact.

Meet your team:

SAP is uniquely positioned to lead the next wave of AI by infusing intelligence directly into the business processes that run the world. Our team's mission is to develop Foundation Models for structured data, starting with the launch and continued evolution of SAP-RPT-1. As the first generation of our relational model portfolio, SAP-RPT-1 represents our commitment to pioneering new research in a domain where SAP's expertise in enterprise data structures provides an unmatched competitive edge. We are looking for innovators to join us in this journey to develop next-generation models with even higher impact, bridging the gap between cutting-edge AI research and the complex, structured reality of global enterprise data.

#LI-CD1

Bring out your best
SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.  
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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, age, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability.

Compensation Range Transparency: SAP believes the value of pay transparency contributes towards an honest and supportive culture and is a significant step toward demonstrating SAP's commitment to pay equity. SAP provides the annualized compensation range inclusive of base salary and variable incentive target for the career level applicable to the posted role. The targeted combined range for this position is 108,100 - 222,800(CAD) USD. The actual amount to be offered to the successful candidate will be within that range, dependent upon the key aspects of each case which may include education, skills, experience, scope of the role, location, etc. as determined through the selection process. Any SAP variable incentive includes a targeted dollar amount and any actual payout amount is dependent on company and personal performance. Please reference this link for a summary of SAP benefits and eligibility requirements: SAP North America Benefits.

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.
Requisition ID: 448372  | Work Area: Software-Design and Development  | Expected Travel: 0 - 10%  | Career Status: Professional  | Employment Type: Regular Full Time   | Additional Locations:  #LI-Hybrid