Chief Machine Learning Engineer - Experience Generation Team
About The Position
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. About the Team The Experience Generation team at SAP accelerates the path from idea to outcome with three generative-AI services: Deep Research & Planning (strategic plans from enterprise + market data), Experience Builder (AI-forged dashboards and micro-apps), and Visual Services (commerce imagery via diffusion). Together they deliver business value across all SAP lines of business, grounded in governed enterprise data and brand standards. Our platform blends a React/Next.js frontend, a Python + FastAPI backend orchestrating LangGraph sub-agents, and a Gardener-managed Kubernetes runtime. With Postgres, Cassandra, HANA Cloud vector engines, and SAP's Generative AI Hub for model governance, we provide an enterprise-grade substrate for controllable, scalable AI workflows. What You'll Do As a Chief Machine Learning Engineer, you'll be a technical leader helping architect, scale, and harden SAP's next generation of generative AI services. You'll drive both design and implementation of ML pipelines, orchestrators, and agentic workflows-turning foundational model research into secure, production-ready enterprise solutions
Requirements
- 12+ years of professional experience in machine learning engineering, software engineering, or applied research roles.
- Deep proficiency in Python and familiarity with Go/TypeScript; experience with distributed systems and orchestration frameworks.
- Strong background in ML/AI, including large language models, embeddings, RAG, and/or multimodal generation.
- Hands-on experience with cloud-native infrastructure (Kubernetes, AWS/Azure) and modern data stores (Postgres, Cassandra, vector DBs).
- Proven track record of delivering production AI systems at scale.
- Strong problem-solving skills and ability to balance innovation with enterprise-grade reliability.
- Experience mentoring engineers and shaping engineering culture.
Responsibilities
- Architect and optimize ML-driven workflows for multi-agent orchestration (LangGraph) across DRP, Experience Builder, and Visual Services.
- Lead technical design discussions, mentor junior engineers, and set engineering standards for reliability and scale.
- Evaluate, fine-tune, and integrate foundation models (text, multimodal, diffusion) through SAP's GenAI Hub and third-party providers (e.g., Amazon Bedrock).
- Design evaluation frameworks and dashboards for quality, safety, and enterprise trust in generative outputs.
- Partner with product teams to define roadmaps and deliver features that serve Sales, Marketing, Finance, HR, and beyond.
- Collaborate with cross-functional SAP AI teams on shared infrastructure, governance, and interoperability.
- Stay at the forefront of ML/AI trends and bring best practices into the team's architecture and execution.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Industry
Professional, Scientific, and Technical Services
Education Level
No Education Listed
Number of Employees
5,001-10,000 employees
