AI/ML Engineer

Role overview Build machine learning capabilities that support products and research in settings where data may be limited, connectivity inconsistent, and decisions have real consequences. As an engineer on a founding team, you will contribute across the model lifecycle—from design and training through inference optimization and integration with product backends—with a focus on practical systems for constrained environments.

Responsibilities - Design, train, and evaluate models for real-world applications. - Build data preparation and feature engineering workflows, and apply sound model validation methods. - Optimize inference and connect models to product backends. - Investigate approaches such as edge AI and decentralized models for constrained settings. - Explain model behavior, uncertainty, and limitations to non-technical partners.

Requirements - Strong Python skills and hands-on experience with a machine learning framework such as TensorFlow, PyTorch, or scikit-learn. - Experience developing and evaluating machine learning models for practical use. - Understanding of preprocessing, feature engineering, and model validation. - Ability to work thoughtfully with sparse or noisy data and communicate model limits clearly. - Strong written communication for asynchronous remote collaboration. - Remote availability from Nigeria; the role is contract-based.

Nice to have - Familiarity with edge AI or TinyML. - Experience with federated learning, privacy-preserving AI, or decentralized model architectures. - Interest in the overlap between AI, decentralized systems, and economic inclusion.