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    Senior Machine Learning and Data Engineer - Basel-Stadt, Schweiz - Talentor Switzerland

    Talentor Switzerland
    Talentor Switzerland Basel-Stadt, Schweiz

    vor 2 Wochen

    Default job background
    Contracting
    Beschreibung

    Partially remote, partially in Basel


    Tasks & Responsibilities:

    • Integrate off-the-shelf open-source embedding models with the system to generate text embeddings from research publications and other text based sources.

    • Design and implement the data processing pipeline to handle the conversion of PDF, XML or other files into a suitable format for text embedding.

    • Set up and maintain the vector database infrastructure, ensuring efficient storage and retrieval of embeddings.

    • Develop and maintain the API for semantic search, allowing for robust querying capabilities.

    • Collaborate with stakeholders to gather requirements and ensure the system meets the needs of the organization.

    • Conduct testing and quality assurance to ensure the reliability and accuracy of the search results.

    • Document the system architecture, API usage, and operational procedures for future reference and maintenance.



    Must Haves:


    The Machine Learning and Data Engineer will be responsible for the end-to-end development and deployment of a semantic search vector database for research purposes and scientific needs. This role requires a combination of skills in machine learning, data engineering, and software development.

    • Strong programming skills, particularly in Python, and experience with machine learning libraries (e.g., TensorFlow, PyTorch)

    • Minimum 7 years Experience with data engineering tasks, including data extraction, transformation, and loading (ETL).

    • Familiarity with vector database technologies (e.g., FAISS, Milvus, Elasticsearch) and database indexing.

    • Knowledge of API development and best practices for scalability and security.

    • Ability to work independently, manage multiple priorities, and communicate effectively with both technical and non-technical stakeholders.

    • English fluent

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