Machine Learning Engineer, SAP

Machine Learning Engineer
United Arab Emirates, Dubai
September 22, 2026
Full Time

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Job Description

SAP is hiring a machine learning engineer to develop and operationalise machine learning and AI solutions from concept through production. The role focuses on building data pipelines, model-serving services, APIs, and evaluation frameworks while supporting forecasting, NLP, recommendation, and generative AI applications. The position also involves MLOps, model monitoring, CI/CD, and scalable enterprise AI systems. 

Qualification: Bachelor’s or Master’s Degree (preferred)

Experience: 1–3+ years 

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Responsibilities

  • Construct and deploy machine learning and AI systems through scalable production environments.
  • Create pipelines for the ingestion, training, inference, API and deployment of models.
  • Contribute to feature engineering, experiments, model optimization, validation and model evaluation.
  • Create language model pipelines which include prompt engineering, vector search, guardrails and retrieval augmented generation.
  • Incorporate CI/CD, monitoring, testing, observability and automated ML model lifecycle management in a process.

Requirements

  • Knowledge in programming with the use of Python and expertise in other programming languages like Java and Go that are needed in building applications.
  • Awareness in machine learning methods and approaches to perform both supervised and unsupervised learning that involve classification and regression.
  • Experience of working with frameworks such as PyTorch and TensorFlow for training, optimising, and inference of the model.
  • Experience of doing data preparation, feature engineering, validation, and offline and online evaluation of the model.
  • Experience of deployment and integration of the model through batch, real-time, and stream processing pipelines.

Preferred Qualifications

  • Knowledge of generative AI, large language models, embeddings, vector databases, prompt engineering, and augmented generation.
  • Knowledge of MLOps, experiment tracking, model versioning, CI/CD, Spark, Kafka, and Airflow.
  • ML production experience, including drift, latency, accuracy, costs, and bias management.
  • Strong ability to balance experimentation with engineering standards and production requirements.
  • 1-3+ years of experience in ML engineering, software engineering, or a related field.