{"id":59113,"url":"https://alion.io/job/integrant-principal-data-scientist-ai-machine-learning-databricks","title":"Principal Data Scientist - AI & Machine Learning (Databricks)","company":{"id":5272,"name":"Integrant","domain":"integrant.com","url":"https://alion.io/company/integrant","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"A","score":90,"open_postings":25,"ghost_share":0.08,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":91,"computed_at":"2026-10-13T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Cairo, 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challenges. \n Engage with clients and stakeholders to understand business needs and translate them into AI and Data Science solutions. \n Design and implement end-to-end Machine Learning and Generative AI solutions. \n Build and optimize Retrieval-Augmented Generation (RAG) systems and intelligent agent-based applications. \n Develop scalable model deployment and monitoring solutions using MLOps best practices. \n Monitor model performance, detect concept drift, and continuously improve deployed systems. \n Collaborate with software engineering teams to productionize AI applications and ensure reliability, scalability, and maintainability. \n Mentor and coach junior Data Scientists and Machine Learning Engineers. \n Lead technical discussions, knowledge transfer sessions, and client-facing AI engagements. \n Stay current with emerging AI, Machine Learning, MLOps, and Generative AI technologies and frameworks.\nRequirements\nEducation & Experience\n7+ years of professional experience, including 5+ years in Data Science, Machine Learning & MLOps\nMSc in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related quantitative discipline.\nExperience mentoring, coaching, or leading technical team members.\nData Science & Machine Learning\nStrong foundation in Machine Learning techniques including Classification, Regression, Clustering, Association Rule Mining, Feature Engineering, and Model Evaluation.\nExperience with Deep Learning concepts and frameworks.\nExtensive hands-on experience with Python and the Data Science ecosystem.\nExperience with one or more ML frameworks such as Scikit-Learn, TensorFlow, Keras, or PyTorch.\nExperience conducting research, experimentation, and hypothesis-driven analysis.\nMLOps & Production AI\nExperience deploying and managing Machine Learning models in production environments.\nExperience monitoring model performance, detecting concept drift, and driving continuous improvements.\nHands-on experience with MLOps practices, CI/CD pipelines, model versioning, experiment tracking, monitoring, and observability.\nExperience deploying AI/ML solutions on cloud platforms such as Azure, AWS, GCP, or Databricks.\nExperience with ML platforms and services including Azure ML, AWS SageMaker, or Google Vertex AI.\nFamiliarity with deployment and serving tools such as MLflow, FastAPI, and Streamlit.\nGenerative AI & Agentic AI\nHands-on experience building Retrieval-Augmented Generation (RAG) solutions and semantic search applications.\nExperience working with Vector Databases such as Pinecone, Weaviate, Chroma, Milvus, or Azure AI Search.\nExperience using LLM orchestration frameworks such as LangChain, LangGraph, or similar technologies.\nExperience working with Agentic AI frameworks such as LlamaIndex, CrewAI, AutoGen, or equivalent.\nExperience implementing MCP (Model Context Protocol), tool calling, and function-calling workflows.\nStrong understanding of prompt engineering techniques and LLM optimization.\nExperience evaluating LLM applications using frameworks such as LangSmith, RAGAS, or similar tools.\nExperience with Embeddings, Vector Retrieval, Semantic Search, Fine-Tuning, and LoRA techniques.\nCloud & Data Engineering\nExperience building large-scale data pipelines on Azure, AWS, or GCP.\nExperience with Databricks and Apache Spark.\nExperience with distributed data processing architectures.\nNice to Have:\nAdvanced AI & Data Science\nReinforcement Learning (RL)\nOptimization techniques, including single-objective and multi-objective optimization\nStochastic Local Search methods\nKnowledge Graphs and Graph Machine Learning.\nLeadership & Consulting\nExperience leading AI initiatives and technical strategy.\nExperience working directly with international clients and stakeholders.\nExperience defining AI architecture, standards, and best practices across teams.\nBenefits\nSalary paid in USD\nSix-month career advancing opportunities\nEmployee parking space\nSupportive and friendly work environment\nPremium medical insurance [employee +family]\nEnglish language development courses\nInterest-free loans paid over 2.5 years\nTechnical development courses\nEmployment referral program\nPremium location in Maadi & Nasr City\nSocial insurance\nOpportunity to travel and work onsite with U.S. customers\nIn-house Technical and English training programs\nFlexible work schedules\nPerks: events, sponsored lunch, game area, rooftop hangout + more!","description_format":"text","description_chars":4944,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[{"language":"English","level":"All levels","optional":true}]},"benefits":["Flexible schedule","Health 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