This position is not for urgent 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)
- Flexible work schedules
- Perks: events, sponsored lunch, game area, rooftop hangout + more!