Clinical NLP Engineer

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.

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 be doing:

• • Augment and synthetically generate and supervise development of datasets
  • Validate training datasets are medically accurate, and implement algorithmic fixes at scale
  • Train new and existing neural network models on medically validated datasets
  • Validate models are medically accurate, and implement algorithmic fixes in production
  • Propose and implement methods to identify and fix medical inaccuracies at all stages of training
  • Advise the Software and DevOps Engineers on the needs of the research platform
  • Advise the Machine Learning Engineers on the needs of the machine learning platform
  • Work with end-to-end cutting edge NLP techniques

This is what you need:

• • Advanced knowledge and experience with medical terminology and principles
  • Prior advanced education in a health related field or experience working with clinical health data
  • Programming proficiency in Python and tooling (numpy, pandas, matplotlib, regex, pytorch, etc)
  • Experience processing and manipulating very large datasets from the command line
  • Experience proposing, building, and applying computational methods to solve medical problems

This would be good to have:

• • Machine learning experience, natural language processing and computer vision
  • Medical Degree or an advanced degree from a field heavy in medical terminology such as biomedical engineering etc.
  • Interest and experience in radiology

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