Senior AI Engineer

5 days ago

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

We're looking for a
Senior AI Engineer
to design, build, and deploy AI and ML solutions for real-world business applications. The ideal candidate has hands-on experience developing both
custom and pre-trained models
(LLMs, vision, NLP, and traditional ML) and delivering them into
production-grade systems
through APIs, web apps, or microservices.

Responsibilities

  • Build, train, and deploy
    machine learning and AI models
    (supervised, unsupervised, deep learning).
  • Integrate and fine-tune
    pre-trained models
    (LLMs, vision, NLP) from providers such as
    OpenAI, Anthropic, AWS Bedrock, Azure AI, or Hugging Face
    .
  • Develop
    end-to-end ML pipelines
    for data processing, training, and inference.
  • Create APIs, web applications, and microservices
    to serve AI models in production.
  • Collaborate with data and software engineering teams to build scalable, maintainable solutions.
  • Optimize models for
    latency, scalability, and cost efficiency
    .
  • Implement model evaluation, monitoring, and performance tracking.
  • Stay current with new AI tools, frameworks, and techniques.

Requirements

  • Proven experience developing and deploying
    ML models
    (regression, classification, NLP, vision).
  • Proficiency in
    Python
    and ML/DL frameworks (
    PyTorch, TensorFlow, Keras
    ).
  • Experience with
    AI APIs and SDKs
    (OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, etc.).
  • Ability to
    develop RESTful APIs, web apps, or microservices
    using
    FastAPI, Flask, or Django
    .
  • Familiarity with
    cloud platforms
    (AWS, Azure, GCP) and
    containerization
    (Docker, Kubernetes).
  • Experience with
    semantic databases
    (e.g., Neo4j, RDF stores, knowledge graphs) and
    relational databases
    (e.g., PostgreSQL, MySQL).
  • Strong understanding of
    version control
    ,
    model evaluation
    , and
    deployment best practices
    .

Preferred

  • Experience with
    MLOps practices
    (CI/CD, model registry, monitoring, governance).
  • Familiarity with
    data orchestration tools
    (Airflow, Prefect, Kafka).
  • Exposure to
    vector databases
    (FAISS, Pinecone, Weaviate) and
    RAG architectures
    .
  • Knowledge of
    prompt engineering
    or
    LLM fine-tuning
    .
  • Experience building
    AI-driven products
    such as chatbots or recommendation systems.

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