AI/ML Engineer (Hybrid NLP + Classification)
This position is available for candidates based in LATAM., Eastern Time overlap for gate and sprint reviewsPart-Time
Salary not disclosed
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Job Details
- Required Skills
- PythonNumpyPandasRESTful APIsMicroservicesscikit-learnNLP
Requirements
- 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
- Precision/recall trade-off framing for catalog mapping
- SAP catalog code domain knowledge
Responsibilities
- 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
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