Tech Stack
Responsibilities
- Own a multimodal ML work-stream from problem definition through experimentation, evaluation, deployment, and iteration.
- Translate clinical and product needs into clear ML objectives, data strategies, model approaches, and success criteria.
- Build and evaluate modern ML systems, including transformers, self-supervised learning, weak supervision, detection, localization, and segmentation.
- Partner with engineering to productionize models, make practical system tradeoffs, and learn from performance after launch.
- Mentor less experienced researchers and engineers through project collaboration, code and experiment reviews, and technical guidance.
Benefits
- 401k
- Equity
- Health Insurance
- Remote Work
Culture
Cross-Functional TeamsMission-DrivenHigh Growth
Requirements
Required: MS, PhD, or equivalent practical experience in Computer Science, Electrical Engineering, Machine Learning, Biomedical Engineering, or a related quantitative field
Regions: Us
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About Rad AI
Industry: healthtech
Size: small
Rad AI is a high-growth, venture-backed healthcare AI company focused on transforming radiology and improving patient care through generative AI and machine learning solutions.
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