Responsibilities
- Design, train, optimize, and ship predictive models for forecasting, deal and quote scoring, classification, anomaly detection, and ranking.
- Build grounded LLM automation and decision-support features for quoting workflows using RAG, faithfulness validation, and tool-calling.
- Own offline and online model evaluation, regression suites, and quality definitions for production systems.
- Manage the ML lifecycle, including CI/CD, model and data versioning, monitoring, drift detection, and retraining.
- Use SQL and large operational datasets to identify business opportunities and create model training data.
- Integrate cloud-native deployments with REST and OData services.
- Mentor less-experienced engineers and act as a senior technical reference point.
Requirements
- Demonstrated expertise in feature engineering, model selection, training, hyperparameter tuning, and evaluation across classical ML and LLM-based systems.
- Proficiency with Python ML tools including pandas, NumPy, scikit-learn, and PyTorch or TensorFlow, plus LLM and RAG frameworks.
- Experience with rigorous model evaluation, including offline metrics, online outcomes, regression suites, and faithfulness checks.
- Experience implementing MLOps practices such as CI/CD for ML, model and data versioning, monitoring, drift detection, and retraining.
- Strong SQL and data-wrangling skills with large, messy operational datasets.
- Experience with Jenkins, GitHub Actions, Elasticsearch, and Kibana for observability.
- Experience with cloud-native deployment and REST/OData integration.
- SAP BTP experience is a plus.
- Exposure to CPQ, quoting, pricing, or sales and revenue processes is a plus.
Benefits
- Flexible working models and a collaborative, inclusive culture focused on health, wellbeing, learning, and personal development.
- Regular full-time employment with expected travel of 0–10%.
- Hybrid work arrangement indicated by the #LI-Hybrid designation.
- Accessibility accommodations are available during the application process.
Categories
About SAP
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