AI / ML Engineer

Role overview

Develop practical machine-learning and AI capabilities for products and internal tools, with an emphasis on features that can be evaluated and operated reliably. The work spans experimentation, data and inference pipelines, product integration, and monitoring, while balancing quality, cost, latency, privacy, and risk.

Responsibilities - Prototype and implement AI or ML features for product workflows. - Compare models and approaches against defined success measures, analyzing quality and failure cases. - Build data preparation and inference pipelines and connect AI services to backend systems. - Track operational considerations such as latency, cost, and reliability, and improve monitoring. - Collaborate with product, engineering, and security partners on responsible use. - Document assumptions and trade-offs, protect sensitive data, and help determine when AI is not an appropriate solution.

Requirements - Practical experience developing AI/ML features or prototypes for production-oriented systems. - Strong Python skills and understanding of model evaluation and failure analysis. - Familiarity with large language models, classical machine learning, or both. - Ability to work with APIs and data pipelines alongside backend engineers. - Clear communication about uncertainty and trade-offs, with sound security and privacy awareness. - Product-minded problem solving.

Nice to have

Experience with PyTorch, scikit-learn, vector search, orchestration libraries such as LangChain or LlamaIndex, cloud ML services, or evaluation frameworks.

Benefits and work setup

Part-time, fully remote work from Egypt, with flexible hours and some collaboration overlap. Cairo office access is available when needed. Listed support includes paid annual and sick leave, performance bonuses, annual salary reviews, learning and certification support, conference opportunities, equipment and internet support, medical insurance, mentorship, and career development.