Machine Learning & Data Engineer
Experis
- Zurich
- CDI
- Temps-plein
- Start date: 1.5.2024
- latest Start Date: 1.7.2024
- Planned duration: 31.12.2024
- Extension (in case of limitation): possible
- Max. Rate: CHF 135.00
- Workplace: Basel, Zürich
- Workload: 100%
- Remote/Home Office: partially remote, partially in Basel
- Travel: no
- Team: 5
- Used Template: CH_Senior Database Manager_IT_CHF_RCM
- Hiring Manager: Agnes Meyder
- Department: pRED Data & Analytics
- Working hours: Standard
- To what extent does this position have access to Roche products or is in a GMP-relevant environment: no
- Is a criminal record extract required: no
- 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.
- 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