Machine Learning Specialist

The role

This senior ML leader will own the complete ML lifecycle and transform the ML function into a scalable, auditable system. You will lead model development, architect reproducible pipelines on AWS, and oversee ground-truth data collection strategies.

What you will do

• Own the complete ML lifecycle
• Lead model development, training, validation, deployment, and performance monitoring
• Architect and maintain reproducible ML pipelines on AWS
• Drive multi-crop expansion and cross-country model generalisation
• Own and enforce Nuru's Model Validation Protocol
• Execute and maintain Model Validation & Sign-Off Reports
• Lead Quarterly Model Governance Reviews
• Enforce the model change protocol
• Establish pre-delivery quality assurance for client-facing datasets
• Design and oversee ground-truth data collection strategies

Required qualifications

• 7+ years of professional experience in machine learning
• Demonstrated expertise in geospatial ML, remote sensing, or agricultural applications
• Hands-on experience with satellite imagery analysis (Sentinel, Planet Labs, or similar), vegetation indices, and time-series modelling
• Proven track record building ML governance and quality systems
• Strong MLOps foundation including version control (Git), model registry, experiment tracking, reproducible training pipelines, and deployment automation
• Experience managing or mentoring small technical teams (2–5 people)
• Comfort working with sparse, noisy, or incomplete datasets and designing robust validation approaches under data scarcity
• Ability to communicate technical complexity clearly and credibly to institutional clients, investors, and non-technical leadership
• Self-directed problem-solver

Nice to have

• Understanding of agricultural systems and smallholder farming contexts in East or Southern Africa
• Experience with AWS cloud infrastructure (S3, EC2/ECS, IAM) for ML workloads
• Familiarity with insurance, credit risk, or financial product design in agricultural or development contexts
• Experience with ensemble methods (Prophet, LSTM, XGBoost), CNNs, and foundation models (SAM or similar) in production settings
• Prior work with ground-truth data collection programmes (crop cuts, field surveys, drone validation)

Benefits

• A company recognised as one of the 30 most promising African startups
• A validated impact: 25,000 farmers served
• Direct collaboration with the CEO and a lean, mission-driven team across four countries
• The opportunity to build the ML governance and infrastructure layer

About the company

Nuru Solutions is a B2B agricultural data intelligence platform operating across Kenya, Malawi, Nigeria, and Somalia. It uses satellite imagery, weather data, ground truth, and machine learning to deliver farm-level intelligence to insurers, lenders, and agribusinesses.