Machine Learning Research Scientist

About Rad AI

We have raised $80+ million to date from venture funds and just closed on our series B financing with investors Khosla Ventures, Gradient (Google’s AI fund) and ARTIS. We’ve also formed a partnership with Google to collaborate on the future of generative AI to redefine healthcare. Currently, more than 1/3 of radiology groups and healthcare systems, including Kaiser Permanente, HCA Healthcare, and Geisinger, now leverage the latest Gen AI advancements from Rad AI. We're recognized as one of the most promising healthcare AI companies by both CB Insights and AuntMinnie. Come join us in transforming healthcare with AI!

Founded by the youngest US radiologist in history, Rad AI empowers physicians with Al to save time, reduce burnout, and improve the quality of patient care. By combining our deep expertise in healthcare and AI and using one of the largest proprietary radiology report datasets in the world, our AI has uncovered hundreds of new cancer diagnoses for patients and reduced the error rate in tens of millions of radiology reports by nearly 50%. 

Why Join Us: 

We’re seeking to add a world-class Machine Learning Scientist and hands-on NLP subject matter expert to join our amazing ML team.

What You’ll Be Doing:

• Develop Advanced Deep Learning Models: Harness the power of deep learning to create sophisticated models capable of performing a range of reasoning and generative tasks, specifically tailored to the nuances of clinical data

• Innovate in Clinical Problem-Solving: Apply your expertise to solve intricate clinical challenges, contributing directly to real-world healthcare advancements

• Collaborative Solution Development: Engage actively with both technical peers and clinical experts to innovate and refine solutions that have a tangible impact in the field of healthcare

• Architect Interdisciplinary Solutions: Play a pivotal role in designing solutions that bridge multiple disciplines. Determine the optimal integration points for machine learning in these solutions and conduct objective evaluations of competing methodologies

• Research Integration and Experimentation: Stay at the forefront of machine learning advancements by reviewing academic papers, designing experiments, and integrating cutting-edge research into our platform

• Mentorship and Collaboration Opportunities: Contribute to the growth of our dynamic Machine Learning Team through mentorship roles and collaborate with our esteemed in-house team of leading clinicians

Who We’re Looking For:

• Preferred PhD in CS or related field

• Experience developing and testing NLP models in a commercial or academic setting

• Experience applying ML solutions to real world problems

• Experience with deep learning …