Scale AI invites applications for a Visiting Student position with a strong interest in Machine Learning in the Healthcare Domain. This is an exciting opportunity for a talented student to contribute to cutting-edge research and development alongside Scale AI's engineering and research teams.
The ideal candidate will have a strong background in Computer Science, Bioinformatics, or a closely related field, and a proven track record of innovative research in Machine Learning and its Applications in Healthcare Domain.
ResponsibilitiesThe Visiting Student will work closely with a mentor on a focused research or engineering project. Responsibilities may include:
- Research & Development Support: Assist in developing and implementing ML models for healthcare applications. This may involve data preprocessing, feature engineering, model training, and rigorous evaluation.
- Project Focus Areas: Contribute to projects within key research areas such as:
- 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.
- Collaboration: Actively participate in team meetings, present progress updates, and engage in collaborative research and development with Scale AI engineers and researchers.
- Currently pursuing a Ph.D. or Master’s degree in Computer Science, Biostatistics, Biomedical Informatics, or a closely related quantitative field.
- 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).
- Excellent problem-solving, communication, and collaboration skills.
PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
About Us:
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
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 equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information.
We comply with the United States Department of Labor's Pay Transparency provision.
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Scale accelerates the development of AI applications by helping machine learning teams generate high-quality ground truth data. Our advanced LiDAR, image, video and NLP annotation APIs allow machine learning teams at companies like OpenAI, Lyft, Pinterest, and Airbnb focus on building differentiated models vs. labeling data.
