Hi there :)
Thanks for checking in to find out about our open position. We´ll provide as much information as possible, but please feel free to reach us if you have further questions. We´ll be happy to see your application, even if there are skills you don't quite master!
About Us
At South Geeks, we engage top-performing Software Engineers, Security Experts, and Data Analysts from Latin America to join our clients' teams worldwide. For over 8 years, we've been helping future-shaping companies scale faster by curating world-class tech talent and building long-lasting, strategic partnerships. We pride ourselves on a people-centered culture that powers innovation, collaboration, and excellence.
About the Client
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. The work runs in 8 Agile-Scrum sprints over 16 weeks, fully remote, with a small senior team operating end to end.
About the Role
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.
Assignment Highlights
- 6 to 10 hours per week during active phases
- 100% remote, Eastern Time overlap for gate and sprint reviews
- BYOD
Key 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.
What You Need to Succeed in This Role
- 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.
Our Team
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.
What We Offer
- 100% remote work
- Payment in USD
This position is available for candidates based in LATAM.
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