Lead Data Scientist - AI & Machine Learning
On-site · Cairo, Cairo, Egypt
Job Summary
Lead Data Scientist will design, develop, and deploy predictive and prescriptive ML/AI solutions, including end-to-end ML and Generative AI deployments, RAG systems, and agent-based applications. Responsibilities include mentoring junior data scientists, leading technical discussions, and engaging with clients to translate business needs into AI/DS solutions. Must stay current with AI/ML/MLOps trends, collaborate with software engineering for productionization, monitor models for drift, and ensure reliability, scalability, and maintainability. Required depth across ML techniques, DL frameworks, Python DS stack, cloud ML platforms, deployment tooling, vector databases, and advanced LLM/LangChain/LangGraph ecosystems.
Required Qualifications
- 10+ years of professional experience in Data Science, Machine Learning & MLOps
- MSc in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or related quantitative discipline
- PhD preferred
- Experience mentoring, coaching, or leading technical team members
- Strong foundation in Machine Learning techniques (Classification, Regression, Clustering, Association Rule Mining, Feature Engineering, Model Evaluation)
- Experience with Deep Learning concepts and frameworks
- Hands-on experience with Python and the Data Science ecosystem
- Experience with ML frameworks such as Scikit-Learn, TensorFlow, Keras, PyTorch
- Experience deploying and managing ML models in production; CI/CD, versioning, experiment tracking, monitoring
- Experience with cloud platforms (Azure, AWS, GCP) and ML platforms (Azure ML, SageMaker, Vertex AI)
- Experience with deployment/serving tools (MLflow, FastAPI, Streamlit)
- Hands-on experience building Retrieval-Augmented Generation (RAG) solutions and semantic search
- Experience with Vector Databases (Pinecone, Weaviate, Chroma, Milvus, Azure AI Search)
- Experience with LangChain, LangGraph; LlamaIndex, CrewAI, AutoGen; MCP
- Prompt engineering and LLM optimization
- Experience evaluating LLM applications (LangSmith, RAGAS)
- Embeddings, Vector Retrieval, Semantic Search, Fine-Tuning, LoRA techniques
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