southgeeks - AI/ML Engineer (Hybrid NLP + Classification)

• Author the AI/ML Architecture Design Document • Recommend an accuracy threshold for the catalog mapping engine. • Build the 4-tier catalog code mapping engine for SAP catalog types. • Implement the AI anomaly detection module. • Design and implement the "Train Model" feedback loop where operator corrections retrain the model. • Wrap the model as a microservice for the main app. • NLP / text classification in Python (scikit-learn or HuggingFace transformers). • AI architecture documentation: a clean model design doc readable by non-technical reviewers. • Rule-based NLP (keyword extraction, regex, scoring logic). • ML classification pipeline (training data preparation, evaluation, tuning). • Anomaly detection in tabular data. • Python data science stack (pandas, numpy, scikit-learn, optionally spaCy). • Model feedback loop design. • API / microservice wrapping of an ML model. • Nice to have: precision/recall trade-off framing for catalog mapping; SAP catalog code domain knowledge. • We strive to create an inspiring and growth-oriented environment where everyone feels valued, heard, and empowered. We promote both personal and professional development, with individualized support for your needs and concerns. We aim to build a space where everyone can thrive.