As a Machine Learning Engineering Intern, you will contribute to advancing AI in life sciences and help build the world’s leading AI diagnostic product for routine clinical use. You will support the design, training, and integration of cutting-edge models that work with medical images, particularly histology slides, which are cornerstones of cancer diagnosis.

You will work at the intersection of AI research and production systems, contributing to robust ML pipelines for medical data analysis. You will gain hands-on experience balancing applied research with practical engineering, helping shape pipelines to analyze data and drive model development.

You will work directly with the Machine Learning Engineering team under the supervision of an ML Engineer, and collaborate with the Data Science team.

In particular, you will:

• Collaborate within a multi-disciplinary team of data scientists, machine learning engineers, product managers, and software engineers.
• Support the research, design, and development of machine learning models tailored to complex and large-scale imaging datasets.
• Contribute to the development of our proprietary ML libraries and workflows in collaboration with the R&D team.
• Contribute to the development and validation of new AI models.
• Participate in the implementation of industrial-scale AI pipelines for medical data analysis, ensuring robustness across production environments.
• Assist in establishing evaluation and monitoring methodologies to ensure model performance, reliability, and interpretability in production.
• Help translate state-of-the-art research into practical solutions.
• Specifically contribute to developing tools to improve the robustness of our models.