Data and Applied Scientist -(AIREE) ARC - AI Research To Capability

We help the world run better
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 youConstant learning, skill growth, great benefits, and a team that wants you to grow and succeed.

Machine Learning Engineer

What you'll do

• At SAP, we amplify the strength of AI technology, fusing it with our robust industry-focused data


• and deep process knowledge. ARC (AI Research to Capability) is the engineering team inside AI


• Research, Experiments and Evaluation (AIREE) that turns new AI research into real capabilities


• for SAP products. We pick up new ideas, pressure-test them with experiments, measure them


• with rigorous evaluations, and ship the winners to production alongside product teams.


• As a Machine Learning Engineer, you will be the bridge between research and production. You


• will take promising experiments, PoCs, and evaluation tooling and turn them into scalable,


• reliable, cloud-native services and APIs that bring AI capabilities - including LLM- and agent-


• based solutions - into the hands of SAP's Lines of Business, product teams, and customers worldwide.

The Role

• Design, build, and deploy scalable machine learning services and APIs on SAP Business


• Technology Platform (BTP) and other cloud platforms.


• Productionize experiments and PoCs - taking research prototypes from the ARC team to


• production-ready state with high availability, performance, and reliability.


• Build and maintain reusable AI engineering foundations: agent harnesses, SDKs, MCP


• servers and tools, and common components that other teams can adopt.


• Operationalize evaluation tooling and observability at scale, so teams know whether their AI


• is ready before release and stays healthy after it ships.


• Develop and maintain CI/CD pipelines, infrastructure-as-code, and MLOps workflows to


• streamline model deployment, versioning, and monitoring.


• Collaborate with data and applied scientists to productionize models, optimize inference


• performance, and integrate capabilities seamlessly into enterprise applications.


• Build robust, secure, and compliant cloud-native applications, leveraging containerization


• (Docker, Kubernetes) and serverless architectures.


• Contribute to architectural decisions for ML and AI platforms, balancing scalability, cost,and developer experience.


• Stay current with advances in MLOps, cloud engineering, Generative AI, and agentic


• systems - and bring what works back into the team's foundations.

What You Bring

• 5 +years of professional experience in software engineering or machine learning


• engineering, with a strong focus on cloud-native development and ML model deployment.


• Bachelor's or master's degree in Computer Science, Artificial Intelligence, Engineering, or


• another relevant discipline.


• Hands-on experience with SAP Business Technology Platform (BTP) is strongly preferred;


• experience with other cloud platforms (AWS, GCP, Azure) is also valuable.


• Proficiency in Python, with experience using ML libraries such as PyTorch, TensorFlow,


• Hugging Face, or similar.


• Solid experience with containerization (Docker), orchestration (Kubernetes), and CI/CD


• tools (e.g., Jenkins, GitHub Actions, GitLab CI).


• Working knowledge of MLOps practices, including model versioning, deployment pipelines,


• monitoring, and lifecycle management.


• Familiarity with REST APIs, microservices architecture, and event-driven systems.


• Understanding of LLM serving frameworks and inference optimization techniques is a plus.


• Exposure to Knowledge Graph technologies (e.g., RDF, SPARQL, property graphs, Cypher)


• or vector databases is a plus.


• Strong communication and collaboration skills, with experience working in agile and cross-


• cultural teams.


• A curiosity to experiment with and adopt emerging technologies and frameworks.

Meet your team

ARC sits inside SAP's AI Research, Experiments and Evaluation (AIREE) organization - thebridge between AI research on one side and LoBs, Joule, and product engineering teams onthe other. We run fast experiments, build evaluation tools and reusable engineering foundations, and carry the winners from research idea to working capability in production. Based in Bangalore, you will join a dynamic, innovative, and globally connected team where engineeringexcellence meets cutting-edge AI research, with abundant opportunities for personal growth,echnical depth, and cross-border collaboration.

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