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HR agency Elevate

Junior AI/ML Engineer

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    Tech Stack / Requirements

    Step into the future of applied AI with this exciting opportunity as a Junior AI/ML Engineer. You’ll contribute to building cutting-edge AI applications such as chatbots, retrieval-augmented generation (RAG) systems, and conversational platforms using Azure AI tools, Prompt Flow, and vector search technologies.

     

    Working under the guidance of experienced engineers, you’ll participate in real-world AI development — from data preparation and model testing to code writing and deployment pipeline support — while gaining hands-on experience with MLOps, CI/CD practices, and responsible AI principles. If you enjoy collaborating within agile teams and want to grow across the AI/ML stack, this role offers a strong foundation in scalable and ethical AI development.

     

    Key Responsibilities:

    • Assist in developing AI/ML applications using Azure AI Services, Prompt Flow, and Azure AI Search (Vector Store).
    • Write clean, testable Python code and participate in peer code reviews.
    • Support the implementation of automated testing and observability in CI/CD pipelines.
    • Help validate and tune models to ensure quality and performance, adhering to responsible AI standards such as fairness and explainability.
    • Contribute to backlog refinement, estimation, and agile ceremonies including sprint planning and retrospectives.
    • Collaborate with MLOps and product teams to support the delivery of AI features.
    • Promote engineering best practices and continuous improvement within the team.
    • Conduct technical spikes for new initiatives under guidance.

     

    Assist with the deployment of training and inference pipelines in Azure ML or Prompt Flow environments.

     

    Skills and Experience:

    • Degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical field.
    • 2+ years of hands-on experience with Python.
    • Foundational understanding of machine learning concepts and model lifecycle.
    • Familiarity with unit/integration testing and core software development principles.
    • Understanding of RESTful API design and version control systems (e.g., Git).
    • Exposure to microservices architecture and distributed systems.
    • Experience with Agile methodologies such as Scrum or Kanban.
    • Effective communication skills and ability to document technical work clearly.
    • Curiosity and a proactive attitude toward learning in a collaborative engineering environment.
    • Awareness of responsible AI concepts, including transparency and data ethics.
    • Familiarity with Docker and containerized development environments (desirable).
    • Exposure to cloud-based ML tools (Azure ML, Prompt Flow, or similar platforms).
    • Understanding of vector search, embeddings, or retrieval techniques (desirable).
    • Ability to assist in configuring ML pipelines and maintaining OpenAPI specifications.
    • Basic knowledge of application authentication protocols (e.g., OAuth 2.0, JWT) and security best practices.

     

    What You’ll Gain:

    • Hands-on experience working with real AI/ML systems and modern cloud-native technologies.
    • Exposure to end-to-end AI/ML development lifecycle in a professional setting.
    • Mentorship from senior engineers and cross-functional collaboration with product, data, and DevOps teams.
    • Opportunities to work on impactful and innovative AI solutions.
    • A supportive work culture that values inclusion, learning, and continuous development