Lead Production ML & AI Systems Engineer

SAP - Germany; Dubai; On-site; AED 420,000 - 660,000; Full time

Job summary

SAP is seeking an experienced AI/ML leader to design and deliver production-grade ML and generative AI systems for our cloud platforms in the UAE region. You will own architecture across data pipelines, training workflows, model serving, and observability, while guiding RAG, embeddings, and guardrails.

You will mentor engineers, shape scalable ML solutions, and drive efficiency, reliability, and performance in live environments with a strong emphasis on responsible AI and cost optimization.

Qualifications

• Expert-level Python programming and software engineering.
• Deep knowledge of ML, DL, and optimization across NLP, ranking, and recommendations.
• Experience designing and operating end-to-end ML systems from data to deployment.
• Hands-on experience with modern ML/LLM tooling and model serving.
• Proficient in embeddings, vector databases, and RAG pipelines.
• Strong MLOps and platform engineering expertise including CI/CD and IaC.
• Architectural understanding of distributed systems and cloud-native ML platforms.

Responsibilities

• Lead design and delivery of production-grade ML and generative AI systems at scale.
• Own architecture across data pipelines, training workflows, and model-serving infra.
• Mentor engineers and drive best practices into reusable patterns and platforms.
• Guide model selection, distributed training, and guardrails for responsible AI.

Skills

Python

Java or Go

ML systems design

End-to-end ML

ML tooling

MLOps & platform engineering

Distributed systems

Tools

PyTorch

TensorFlow

scikit-learn

Job description

SAP is seeking an experienced AI/ML leader to design and deliver production-grade ML and generative AI systems for our cloud platforms in the UAE region. You will own architecture across data pipelines, training workflows, model serving, and observability, while guiding RAG, embeddings, and guardrails.

You will mentor engineers, shape scalable ML solutions, and drive efficiency, reliability, and performance in live environments with a strong emphasis on responsible AI and cost optimization.