Machine Learning Specialist

📋 Description

• Own the complete ML lifecycle from development to deployment and monitoring for production models.
• Architect and maintain reproducible ML pipelines on AWS with version control and proper
• Drive multi-crop expansion and cross-country generalisation across diverse agroecological zones.
• Lead governance, validation, and quality initiatives for model reporting and sign-offs.
• Establish pre-delivery QA for client-facing datasets and analytics.

🎯 Requirements

• 7+ years in machine learning with geospatial ML, remote sensing, or agricultural applications.
• Hands-on satellite imagery analysis (Sentinel, Planet Labs), vegetation indices, time-series
• Proven ML governance and quality systems experience; strong MLOps foundation (Git, model registry
• Experience managing or mentoring small technical teams (2–5 people).
• Comfort with sparse/noisy datasets and robust validation under data scarcity.
• Ability to communicate complex technical concepts to institutional clients and leadership.

🎁 Benefits

• A company recognised as one of the 30 most promising African startups
• Validated impact: 25,000 farmers served
• Direct collaboration with the CEO across four countries
• Opportunity to build ML governance and infrastructure for critical African agrifinance data platform