Machine Learning Engineer (Dubai, Dubai, AE, 118353)

SAP
Dubai
Workplace: HybridFull timeFunction: Data Science & Machine LearningExperience: 1-3 yearsSkills: ["Ownership","Collaboration","Problem-solving","Handling ambiguity"]

Build and operationalize end-to-end machine learning and AI capabilities from idea through production. Develop data pipelines, training and inference workflows, model-serving services, APIs, and evaluation frameworks for use cases including recommendations, forecasting, anomaly detection, classification, NLP, semantic search, and generative AI. Improve LLM workflows with RAG, vector search, guardrails, and quality evaluation, while strengthening CI/CD, monitoring, observability, testing, and model lifecycle automation for reliable, enterprise-ready systems.

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FursaFursa
SAP
SAP
2 hours ago

Machine Learning Engineer (Dubai, Dubai, AE, 118353)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live

Job Summary

Build and operationalize end-to-end machine learning and AI capabilities from idea through production. Develop data pipelines, training and inference workflows, model-serving services, APIs, and evaluation frameworks for use cases including recommendations, forecasting, anomaly detection, classification, NLP, semantic search, and generative AI. Improve LLM workflows with RAG, vector search, guardrails, and quality evaluation, while strengthening CI/CD, monitoring, observability, testing, and model lifecycle automation for reliable, enterprise-ready systems.
Location: Dubai
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Entry level

Key Responsibilities

  • •Build and operationalize machine learning and AI capabilities from idea to production, delivering measurable product value.
  • •Develop data pipelines, training and inference workflows, model-serving services, APIs, and evaluation frameworks for ML and generative AI use cases.
  • •Perform feature engineering, experiment design, model tuning, and offline/online validation, integrating models into scalable product architectures.
  • •Improve LLM-based workflows using prompt design, retrieval-augmented generation, vector search, guardrails, and response quality evaluation.
  • •Strengthen AI engineering through CI/CD, monitoring, observability, testing, and model lifecycle automation to ensure reliability, cost awareness, security, and enterprise readiness.
Travel: Low travel

Key Requirements

  • •Strong programming skills in Python and working knowledge of Java or Go for production-grade services and APIs.
  • •Solid ML fundamentals across supervised and unsupervised methods (classification, regression, clustering, ranking, recommendation).
  • •Hands-on deep learning experience with frameworks such as PyTorch or TensorFlow for training, fine-tuning, and inference.
  • •Experience preparing data, performing feature engineering, and validating/evaluating models using offline and online metrics.
  • •Experience deploying/integrating ML models into production using batch, real-time, or streaming pipelines.
Experience:1-3 years
Skills:OwnershipCollaborationProblem-solvingHandling ambiguity
Tech Stack:PythonJavaGoPyTorchTensorFlowLLMsEmbeddingsVector databasesPrompt engineeringRetrieval-augmented generationCI/CDSparkKafkaAirflowFeature storesAPIs

Company Brief

SAP
Global enterprise software company best known for ERP systems and business applications covering finance, supply chain, procurement, HR, analytics, and customer management for large organizations.
Industry: Enterprise Software
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Walldorf, Germany
Founded: 1972
Glassdoor
Glassdoor: 4.1
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