Scale AI is looking to solve problems in the healthcare domain by developing reliable AI systems. This involves applying Machine Learning to patient data, clinical notes, and medical chatbots to improve safety and factual accuracy, forecasting health behaviors and outcomes, and addressing bias and fairness in clinical AI algorithms.
Requirements
- Strong foundational knowledge of Machine Learning principles and algorithms.
- Experience with relevant programming languages (Python) and ML frameworks (e.g., PyTorch, TensorFlow).
- Demonstrated interest or experience in Healthcare or Biomedical applications, particularly involving clinical data (e.g., EHRs, medical images, genomics).
Responsibilities
- Assist in developing and implementing ML models for healthcare applications.
- This may involve data preprocessing, feature engineering, model training, and rigorous evaluation.
- Applying Natural Language Processing (NLP), Multi-modal AI, or Large Language Models (LLMs) to patient data, clinical notes, or medical chatbots to improve safety and factual accuracy.
- Developing predictive models using Electronic Health Records (EHRs) or non-clinical data to forecast health behaviors and outcomes (e.g., medication adherence, disease progression).
- Investigating methods to address bias and fairness in AI algorithms used in clinical settings.
- Actively participate in team meetings, present progress updates, and engage in collaborative research and development with Scale AI engineers and researchers.
Other
- Currently pursuing a Ph.D. or Master’s degree in Computer Science, Biostatistics, Biomedical Informatics, or a closely related quantitative field.
- Excellent problem-solving, communication, and collaboration skills.
- Our policy requires a 90-day waiting period before reconsidering candidates for the same role.
- We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace.
- We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities.
