Rad AI applies deep learning to radiology in order to save lives and reduce the cost of healthcare. We believe that strong teams working closely together create audacious companies that transform our world for the better.

Our world-class team of engineers is building and deploying products that will make a difference in millions of people’s lives. You’ll be an early team member, helping us shape the long-term vision for Rad AI’s future. We're seeking another valuable Machine Learning Engineer (NLP focus) to join our strong and growing remote team.

Here at Rad AI, we’re focused on transparency, inclusion, close collaboration, and building an incredible team. Come and help us make a difference!

This is what you'll do

  • Develop high precision classifiers and tools leveraging machine learning, regression and rule-based models
  • Create tools to scale and visualize systems in order to understand what they are doing and guide their improvement
  • Read papers and devise experiments with the intent of incorporating new research into our platform
  • Advise the Software and DevOps Engineers on the needs of the research platform

This is what you need

  • Preferred PhD or Masters in CS or related field, or equivalent experience
  • At least two years of prior experience, with consideration taken for extensive academic projects
  • Experience developing and testing NLP models in a commercial setting
  • Experience applying both supervised and unsupervised methods to real world datasets
  • Solid fundamentals in algorithms, math, and probability theory
  • Experience using modern deep learning frameworks (such as Tensorflow)
  • Extensive programming skills, with a focus on Python

This would be nice to have

  • Experience working at an early stage startup
  • Prior academic paper publishing success
  • Experience in a HIPAA compliant environment
  • Experience applying machine learning to clinical health data

Thank you for your interest. We look forward to hearing from you.

At Rad AI, we value diversity and provide equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.


Machine Learning
PyTorch (Machine Learning Library)
Natural Language Processing
Deep Learning
Python (Programming Language)
Clinical Research
Clinical Data Management