Principal Data Scientist - AI & Machine Learning

Job description

# Principal Data Scientist - AI & Machine Learning > Integrant · Cairo, Egypt (Hybrid) · — · Posted 2026-06-10 **Workplace:** hybrid **Department:** Software Development ## Description We Are Hiring! Integrant is looking for game changers to join our team as "Data Scientist - AI & Machine Learning" with below roles and responsibilities: - Use mathematics, statistics, machine learning, and artificial intelligence techniques to extract knowledge and insights from structured, semi-structured, and unstructured data. - Design, develop, evaluate, and deploy predictive and prescriptive machine learning models. - Conduct open research and experimentation to develop innovative solutions for complex client challenges. - Engage with clients and stakeholders to understand business needs and translate them into AI and Data Science solutions. - Design and implement end-to-end Machine Learning and Generative AI solutions. - Build and optimize Retrieval-Augmented Generation (RAG) systems and intelligent agent-based applications. - Develop scalable model deployment and monitoring solutions using MLOps best practices. - Monitor model performance, detect concept drift, and continuously improve deployed systems. - Collaborate with software engineering teams to productionize AI applications and ensure reliability, scalability, and maintainability. - Mentor and coach junior Data Scientists and Machine Learning Engineers. - Lead technical discussions, knowledge transfer sessions, and client-facing AI engagements. - Stay current with emerging AI, Machine Learning, MLOps, and Generative AI technologies and frameworks. ## Requirements **Education & Experience** - 7+ years of professional experience, including 5+ years in Data Science, Machine Learning & MLOps - MSc in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related quantitative discipline. - Experience mentoring, coaching, or leading technical team members. **Data Science & Machine Learning** - Strong foundation in Machine Learning techniques including Classification, Regression, Clustering, Association Rule Mining, Feature Engineering, and Model Evaluation. - Experience with Deep Learning concepts and frameworks. - Extensive hands-on experience with Python and the Data Science ecosystem. - Experience with one or more ML frameworks such as Scikit-Learn, TensorFlow, Keras, or PyTorch. - Experience conducting research, experimentation, and hypothesis-driven analysis. **MLOps & Production AI** - Experience deploying and managing Machine Learning models in production environments. - Experience monitoring model performance, detecting concept drift, and driving continuous improvements. - Hands-on experience with MLOps practices, CI/CD pipelines, model versioning, experiment tracking, monitoring, and observability. - Experience deploying AI/ML solutions on cloud platforms such as Azure, AWS, GCP, or Databricks. - Experience with ML platforms and services including Azure ML, AWS SageMaker, or Google Vertex AI. - Familiarity with deployment and serving tools such as MLflow, FastAPI, and Streamlit. **Generative AI & Agentic AI** - Hands-on experience building Retrieval-Augmented Generation (RAG) solutions and semantic search applications. - Experience working with Vector Databases such as Pinecone, Weaviate, Chroma, Milvus, or Azure AI Search. - Experience using LLM orchestration frameworks such as LangChain, LangGraph, or similar technologies. - Experience working with Agentic AI frameworks such as LlamaIndex, CrewAI, AutoGen, or equivalent. - Experience implementing MCP (Model Context Protocol), tool calling, and function-calling workflows. - Strong understanding of prompt engineering techniques and LLM optimization. - Experience evaluating LLM applications using frameworks such as LangSmith, RAGAS, or similar tools. - Experience with Embeddings, Vector Retrieval, Semantic Search, Fine-Tuning, and LoRA techniques. Nice to Have: **Advanced AI & Data Science** - Reinforcement Learning (RL) - Optimization techniques, including single-objective and multi-objective optimization - Stochastic Local Search methods - Knowledge Graphs and Graph Machine Learning. **Cloud & Data Engineering** - Experience building large-scale data pipelines on Azure, AWS, or GCP. - Experience with Databricks and Apache Spark. - Experience with distributed data processing architectures. **Leadership & Consulting** - Experience leading AI initiatives and technical strategy. - Experience working directly with international clients and stakeholders. - Experience defining AI architecture, standards, and best practices across teams. ## Benefits - Salary paid in USD - Six-month career advancing opportunities - Employee parking space - Supportive and friendly work environment - Premium medical insurance \[employee +family\] - English language development courses - Interest-free loans paid over 2.5 years - Technical development courses - Planned overtime program (POP) - Employment referral program - Premium location in Maadi & Nasr City - Social insurance - Opportunity to travel and work onsite with U.S. customers - In-house Technical and English training programs - Dedicated learning time (check out our [4Plus1 Program](https://www.integrant.com/toughest-problem-in-outsourced-software-development-solved/)) - Flexible work schedules - Perks: events, sponsored lunch, game area, rooftop hangout + more! ## Apply [Apply at Integrant](https://apply.workable.com/integrant/j/C9BC4E94A9/apply) --- Powered by [Workable](https://www.workable.com)