Develop machine learning models and inference pipelines for practical applications in the SAP ecosystem (e.g., prioritization, classification, decision enrichment, RAG)
Design and evaluate AI agent architectures with LLMs, using frameworks like Crew.ai, LangChain, AutoGen
Work with the data and engineering teams to prepare features, ingest historical data, and perform exploratory analysis
Implement recommendation, classification, clustering, or language generation models according to project goals
Evaluate risks, fairness, explainability, and performance metrics of models in production
Requirements
Solid experience as a Data Scientist, with a portfolio of models applied in a real-world context
Knowledge of generative AI and agent frameworks (e.g., LangChain, Crew.ai, AutoGen, Haystack)
Proficiency in Python, scikit-learn, transformers, Hugging Face, Pandas, NumPy
Ability to work with both classic models and LLMs; knowledge of prompt engineering, embeddings, vectors, and contexts
Familiarity with Databricks, MLflow, and model versioning
Advanced or fluent English
It will be a plus: experience developing RAG pipelines with structured and unstructured data
It will be a plus: experience with SAP integrations or a proven willingness to immerse in this universe
It will be a plus: knowledge of document search, chunking, embeddings, fine-tuning, and feedback loops in production systems
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