About the position
We are looking for a part-time AI/ML Engineer to design and build the AI component of the platform: a hybrid rule-based plus ML system that maps contractor free-text into a 4-tier SAP catalog hierarchy, flags anomalies, and learns from operator corrections. This is a 4-month engagement and your active participation spans SP0 through SP3 (W1 to W10), at roughly 6 to 10 hours per week during active phases. The work runs in 8 Agile-Scrum sprints over 16 weeks, fully remote, with a small senior team operating end to end. Our client is a Fortune 500 global energy company running a strategic initiative to migrate historical Plant Maintenance data into SAP S/4HANA through a governed, auditable web application integrated with SAP CPI.
Responsibilities
• Author the AI/ML Architecture Design Document at Gate 0 (W2). This is the W2 blocker for the whole project and must be readable by a non-technical PM.
• Recommend an accuracy threshold for the catalog mapping engine.
• Build the 4-tier catalog code mapping engine for SAP catalog types (Object Part B, Symptom C, Cause 5, Activity A).
• 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.
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.
Nice-to-haves
• precision/recall trade-off framing for catalog mapping
• SAP catalog code domain knowledge
Benefits
• Long-term projects
• 100% remote work
• Payment in USD
• Paid Time Off (PTO)
• Work from Home (WFH) & Training reimbursement
• English lessons
• Technical training
• Career coaching
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