Machine Learning Engineer
SAP View all jobs
- Dubai
- Permanent
- Full-time
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.What you’ll buildIn this role, you'll build and operationalize machine learning and AI capabilities that from idea to production and deliver measurable product value. You'll develop data move pipelines, training and inference workflows, model-serving services, APIs, and evaluation frameworks for use cases such as recommendation, forecasting, anomaly detection, classification, NLP, semantic search, and generative AI.Your work will include feature engineering, experiment design, model tuning, offline and online validation, and integration of models into scalable product architectures. You'll help improve LLM-based workflows, including prompt design, retrieval-augmented generation, vector search, guardrails, and response quality evaluation. You’ll also strengthen the engineering backbone around AI through CI/CD, monitoring, observability, testing, and model lifecycle automation so solutions are reliable, cost-aware, secure, and ready for enterprise scale.What you bring:
- You bring strong programming skills in Python, along with working knowledge of Java or Go, for building production-grade services and APIs
- You have a solid understanding of machine learning fundamentals, including supervised and unsupervised methods such as classification, regression, clustering, ranking, and recommendation systems
- You have hands-on experience with deep learning frameworks (e.g., PyTorch or TensorFlow) for model training, fine-tuning, and inference
- You demonstrate strong capabilities in data preparation, feature engineering, data validation, and model evaluation using appropriate offline and online metrics
- You have experience building, deploying, and integrating ML models into production systems through batch, real-time, or streaming pipelines
- You are familiar with generative AI concepts, including LLMs, embeddings, vector databases, prompt engineering, and retrieval-augmented generation, and how to apply them in practical use cases
- You bring working knowledge of MLOps and modern data infrastructure, including experiment tracking, model versioning, CI/CD, and tools such as Spark, Kafka, Airflow, and feature stores
- You have experience operating ML systems in production, including monitoring for drift, latency, accuracy, cost, bias, and performing debugging and failure analysis to ensure reliability and business impact
- You have 1-3+ years of experience in machine learning engineering, software engineering, or a related field, with a track record of deploying models into production
- You are passionate about building reliable, scalable ML systems and take ownership of delivering end-to-end solutions
- You balance experimentation with engineering rigor, making thoughtful trade-offs to ensure models are both innovative and production-ready
- You are a collaborative problem-solver who thrives in ambiguous environments and is motivated by delivering measurable business impact
SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.We win with inclusion
SAP’s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone – regardless of background – feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world.SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: Careers@sap.com.For SAP employees: Only permanent roles are eligible for the , according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training.Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements.Successful candidates might be required to undergo a background verification with an external vendor.AI Usage in the Recruitment ProcessFor information on the responsible use of AI in our recruitment process, please refer to our .Please note that any violation of these guidelines may result in disqualification from the hiring process.Requisition ID: 450276 | Work Area: Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations: #LI-Hybrid