# AI Research Engineer - Innovation Team
Join ScreenPoint Medical's Innovation team to develop foundation models and state-of-the-art AI solutions for breast cancer care. You will design and implement downstream AI models that operationalize clinical endpoints, working with vision transformer networks and vision-language models.
## Responsibilities
- Design and implement downstream AI models that operationalize clinical endpoints using outputs from foundation models
- Translate clinical study designs and outcome definitions into clear modeling tasks and evaluation frameworks in collaboration with Clinical Scientists
- Define and apply consistent modeling and evaluation approaches across multiple biomarkers and imaging modalities
- Collaborate closely with the AI Algorithm Lead to ensure robust integration between foundation models, MLOps infrastructure, and downstream biomarker models
- Guide and review modeling approaches developed by AI Research Scientists, providing technical feedback and mentorship
- Perform in-depth model analysis, including calibration, subgroup performance, and failure-mode assessment
## Required Qualifications
- MSc or PhD in Computer Science, Machine Learning, Biomedical Engineering, Applied Mathematics, Physics, or related technical field
- At least 5 years of experience developing AI or machine learning models in medical imaging or clinical research context
- Proven ability to translate clinical or scientific questions into appropriate modeling approaches (classification, risk prediction, longitudinal modeling)
- Experience working with multimodal data (imaging combined with clinical or pathology data)
- Strong understanding of model evaluation, calibration, robustness, and subgroup performance in real-world datasets
- Familiarity with foundation models and downstream fine-tuning or adaptation strategies
- Proficiency in Python and deep learning frameworks, and experience in Linux-based environments
## Preferred Qualifications
- Experience in NLP with LLMs or VLMs