Data Engineer - PyTorch Contract

You will be responsible for designing, building and maintaining data pipelines that support machine learning use cases. The project is particularly heavy on PyTorch for data loading and dataset management, and you will be working with large volumes of files stored in cloud object storage. You'll collaborate closely with technical stakeholders and domain experts, managing data that is specific to the life sciences space., This role is not looking for a specialist ML Engineer. Candidates should have practical exposure to PyTorch or similar frameworks (TensorFlow can be considered), such as supporting ML pipelines or delivering a substantial project over 6-12 months. Experience limited to Pandas or NumPy alone would not be suitable.

This is a data engineering role rather than an ML Engineer or Data Scientist position. The successful contractor will be comfortable operating close to machine learning workflows, particularly working with PyTorch in a cloud environment, but the core responsibility remains data engineering at scale., Strong Python development Extensive experience with cloud object / blob storage for unstructured data Experience with Google Cloud Storage (preferred) or AWS S3 Hands-on experience using PyTorch, particularly for data loading and dataset management Five or more years of commercial experience in data engineering or cloud data platforms

Desired Experience GCP experience, including BigQuery Strong SQL skills across relational databases such as Microsoft SQL Server or PostgreSQL Understanding of memory management in data-intensive systems

Nice to Have Experience with additional GCP services such as Cloud Run, Cloud SQL or Cloud Scheduler Exposure to machine learning workflows in a production environment Background or interest in pharma or life sciences, * python

• gcp
• data engineering
• pytorch

Hybrid working, London-based, £700 per day inside IR35.

For more information, please apply or contact Harnham for a confidential discussion.