Principal Machine Learning Engineer

• Compensation: USD 198,200 - USD 420,000 - yearly

Be part of SAP's expert community, influencing global AI initiatives and mentoring talent to deliver impactful innovations.

You will architect ML solutions, lead deployment at scale, and ensure compliance with performance and security standards. You'll act as a trusted advisor and contribute to SAP's AI strategy.

What you'll bring

You have deep expertise in advanced ML system architecture, scalable model deployment, and ML platform capabilities. You are expected to have a solid understanding of modern AI application development, including large language models, retrieval-augmented generation (RAG), prompt engineering, vector search, agent workflows, and model evaluation techniques. You are the technical partner who can bridge the gap between customer requirements and product capabilities and are comfortable working directly with stakeholders, gathering requirements, clarifying ambiguous requests, and proposing solutions that maximize customer value.

Your ability to guide teams, optimize workflows, and connect emerging ML advancements to business needs is what this level is built around. Experience with large-scale ML architecture design, advanced MLOps and observability, model governance and explainability, and optimization across performance and cost dimensions is expected. Technical mentorship and the ability to set standards that others follow are also part of what you'll bring.

What you'll build

You'll lead the design and optimization of large-scale ML systems (LLM capabilities and infrastructure), shape cutting-edge infrastructure, mentor engineers, and define architectural and operational standards. Ensuring ML solutions meet business, performance, scalability, and governance requirements, while advancing the adoption of modern ML techniques, is a central part of the role. You'll influence technical direction across products, enable safe experimentation, and ensure systems are production-ready and aligned with product objectives.

Where you belong

You'll shape how ML engineering is practiced across teams and products, not just within your immediate group. The role requires both technical depth and the ability to influence people who don't report to you. Mentoring engineers is an explicit expectation, and the standards you set will affect work well beyond your direct area. If you've reached the point where your value comes as much from what you enable in others as from what you build yourself, this level reflects that.

Skills used in this role include:
Design & Architecture, Leadership & Impact, Managing ambiguity, Engineering Excellence, Quality Mindset, Context engineering, AI output quality assurance, Agentic AI day-to-day practice, AI-Assisted Automation and Prototyping, AI adoption capability, Learning Agility, Collaboration, Complex problem solving, Creative thinking, Effective communication

Equal Employment Opportunity (EEO) Statement

Our company does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor.

10+ years of software engineering experience with a track record of delivering complex systems

Bachelor's degree in Computer Science, Mathematics, Physics, or related field

Hands-on experience with AI/ML in production environments, including large language models (LLM), retrieval-augmented generation (RAG), prompt engineering, vector search, agent workflows, and model evaluation techniques

Expertise in…