Senior Machine Learning and Data Engineer

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