Senior Machine Learning Specialist – Agricultural Data

About the role

Nuru Solutions is scaling its B2B agricultural data intelligence platform across Kenya, Malawi, Nigeria, and Somalia. The company seeks a senior Machine Learning Specialist to own the integrity, reproducibility, and continuous improvement of all production models.

Key responsibilities

• Lead the full ML lifecycle: development, training, validation, deployment, and performance monitoring for all production models.
• Design and maintain reproducible, version‑controlled ML pipelines on AWS, ensuring auditability and scalability.
• Drive multi‑crop and cross‑country model generalisation, expanding from maize to beans, sorghum, potatoes, and horticultural crops.
• Implement and enforce a rigorous Model Validation Protocol, produce quarterly governance reviews, and manage model change documentation.
• Oversee ground‑truth data collection strategies using KoboToolbox, drone imagery, and field surveys across four countries.
• Mentor junior data scientists, set standards for code quality, documentation, and peer review.

Required profile

• 7+ years of professional experience in machine learning, with a focus on geospatial or agricultural applications.
• Proven ability to build ML governance and quality systems in environments lacking formal processes.
• Experience leading small technical teams (2–5 people) in fast‑moving, resource‑constrained settings.
• Comfort working with sparse, noisy datasets and designing robust validation under data scarcity.

Required skills

• Machine Learning, Geospatial ML, Remote Sensing, Satellite Imagery Analysis (Sentinel, Planet Labs), Vegetation Indices, Time‑series Modelling.
• MLOps foundations: Git, model registry, experiment tracking, reproducible pipelines, deployment automation.
• AWS cloud services (S3, EC2, ECS, IAM).
• Advanced modelling tools: Prophet, LSTM, XGBoost, CNNs, foundation models such as SAM.
• Ground‑truth collection tools: KoboToolbox, drone imagery.

What we offer

• Recognition as one of the 30 most promising African startups.
• Impactful work serving 25,000 smallholder farmers.
• Direct collaboration with the CEO and a lean, mission‑driven team across four countries.
• Opportunity to build the ML governance layer for a critical African agrifinance data platform.