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
- 10+ years of professional experience, including 7+ years in Data Science, Machine Learning & MLOps
- MSc in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related quantitative discipline
- PhD is preferred, in related field.
- 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!
