Senior Machine Learning Engineer

4 days ago

Qesm El Maadi Cairo, Egypt Zeidex Full time 120,000 - 240,000 per year

About the Role

We are seeking a
Senior AI Engineer
with strong experience in
Big Data processing
,
Matching Logic / Recommendation Systems
, and
Large Language Models (LLMs)
to join our AI core team. You'll lead the design and deployment of data-driven, intelligent systems that power personalized insights, matching algorithms, and conversational AI capabilities across our platform.

This role requires deep technical expertise in scalable data processing, advanced ML pipelines, and modern AI frameworks — with a hands-on mindset to build, experiment, and ship production-ready models that impact real users.

Key Responsibilities

  • Design and implement
    AI-driven matching systems
    leveraging behavioral, semantic, and contextual data to improve personalization and recommendations.
  • Develop and optimize
    machine learning and LLM pipelines
    for large-scale, real-time applications.
  • Lead data ingestion, transformation, and feature engineering workflows from
    structured and unstructured big data sources
    .
  • Integrate
    LLM-based reasoning and embeddings
    with
    vector databases
    for context-aware search and retrieval.
  • Architect and deploy
    end-to-end AI solutions
    using cloud and MLOps tools (e.g., AWS/GCP, Docker, Airflow, MLflow).
  • Collaborate with cross-functional teams (data, product, and backend) to translate business goals into AI-driven systems.
  • Conduct research and experimentation to continuously improve model accuracy, latency, and interpretability.
  • Mentor junior engineers and contribute to the evolution of our AI/ML architecture.

Requirements

  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Engineering, or related field.
  • 5+ years of experience in
    AI/ML engineering
    , with production-grade deployments.
  • Proven experience in
    Big Data frameworks
    such as
    Spark
    ,
    Hadoop
    ,
    Kafka
    , or
    Databricks
    .
  • Expertise in
    Python
    and ML frameworks like
    PyTorch
    ,
    TensorFlow
    , or
    Scikit-learn
    .
  • Strong knowledge of
    LLMs
    ,
    embedding models
    , and
    transformer-based architectures
    (OpenAI, Hugging Face, etc.).
  • Hands-on experience building
    matching, ranking, or recommendation systems
    .
  • Proficiency in
    data modeling, feature engineering
    , and
    pipeline automation
    .
  • Experience with
    vector databases
    (e.g., Pinecone, FAISS, Weaviate, Milvus).
  • Strong problem-solving, analytical, and communication skills.

Preferred Skills

  • Experience integrating
    LLMs with external data sources
    using
    RAG (Retrieval-Augmented Generation)
    architectures.
  • Background in
    knowledge graphs
    ,
    semantic search
    , or
    entity matching
    .
  • Familiarity with
    MLOps
    and
    CI/CD
    workflows for AI deployment.
  • Experience in
    multi-modal AI
    (text, image, audio) is a plus.
  • Prior work in
    behavioral analytics
    ,
    psychometrics
    , or
    personalization systems
    .

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