Machine Learning Engineer

Role overview Help deliver an applied project building language understanding and information retrieval systems. This is hands-on engineering focused on practical outcomes: developing and tuning machine learning components, integrating them with existing services, and delivering production-ready code.

Responsibilities - Develop and optimize pipelines for language understanding and retrieval. - Design, train, or fine-tune models for text processing, similarity, and reasoning. - Integrate machine learning components with backend systems and APIs. - Work with the technical team to produce clean, scalable implementations. - Document your approach and deliver production-ready code.

Requirements - Hands-on experience completing at least one or two machine learning or NLP projects end to end. - Strong Python skills and practical experience with frameworks such as PyTorch, TensorFlow, or scikit-learn. - Understanding of large language models and retrieval-based AI. - Ability to work independently, manage timelines, and deliver dependable results. - Good communication skills and attention to detail.

Nice to have Experience with LangChain, LlamaIndex, or similar tools; familiarity with vector databases such as pgvector, Qdrant, or Chroma; or basic Arabic NLP knowledge.

Benefits and work setup Project-based, remote engagement with an immediate start.