20 hours ago
Dubai, United Arab EmiratesEntry Level / Mid Level
Responsibilities
- Build and operationalize machine learning and AI capabilities from ideation through production.
- Develop data movement pipelines, training and inference workflows, model-serving services, APIs, and evaluation frameworks.
- Implement feature engineering, experiment design, model tuning, offline and online validation, and model integration into scalable product architectures.
- Improve LLM workflows through prompt design, retrieval-augmented generation, vector search, guardrails, and response-quality evaluation.
- Strengthen AI engineering infrastructure through monitoring, observability, testing, and model lifecycle automation.
- Operate production ML systems by monitoring drift, latency, accuracy, cost, and bias and performing debugging and failure analysis.
Requirements
- 1–3+ years of experience in machine learning engineering, software engineering, or a related field, with experience deploying models into production.
- Strong programming skills in Python and working knowledge of Java or Go for production-grade services and APIs.
- Understanding of supervised and unsupervised machine learning, including classification, regression, clustering, ranking, and recommendation systems.
- Hands-on experience with PyTorch or TensorFlow for model training, fine-tuning, and inference.
- Experience with data preparation, feature engineering, data validation, and model evaluation using offline and online metrics.
- Experience building, deploying, and integrating ML models through batch, real-time, or streaming pipelines.
- Familiarity with generative AI concepts including LLMs, embeddings, vector databases, prompt engineering, and retrieval-augmented generation.
- Working knowledge of MLOps and modern data infrastructure, including experiment tracking, model versioning, CI/CD, Spark, Kafka, Airflow, and feature stores.
- Ability to build reliable, scalable, production-ready solutions and make thoughtful trade-offs between experimentation and engineering rigor.
Benefits
- Regular full-time employment.
- Flexible working models with a hybrid work arrangement indicated.
- Expected travel of 0–10%.
- Inclusive workplace with health and well-being support, accessibility accommodations, and professional development opportunities.
- Successful candidates may undergo background verification with an external vendor.
Tech Stack
Categories
About SAP
SAP builds enterprise application software and cloud services for finance, procurement, supply chain, human resources, and analytics, sold through subscriptions, licenses, and support. Its portfolio includes SAP S/4HANA, SAP Business Technology Platform, SAP Ariba, and SAP SuccessFactors. Founded in 1972 and headquartered in Walldorf, Germany, SAP is a public company listed on the NYSE and Frankfurt (ETR) and serves enterprises and public-sector organizations worldwide.