Senior ML Scientist, Healthcare AI & Recommender Systems

Go REcruitment; Vancouver; On-site; USD 57,000 - 101,000; Full time

Job description

Do you want to do cutting edge research for a healthcare nonprofit dedicated to improving healthcare for all, especially for the poor and vulnerable? What about a startup dedicated to improving patient outcomes? Providence Digital Innovation Group (DIG) is looking for an applied scientist to join us as we work to personalize healthcare and improve patient outcomes and potentially spin out a new healthcare AI focused startup to continue the work.

We are looking for a scientist with a breadth of understanding across ML topics, but a deep background in recommender systems, and an interest in doing cutting edge research and submitting papers and talks to top-tier conferences. You will be working on a greenfield project with substantial ability to influence the project’s overall direction and work with cutting edge technology without legacy systems to slow you down. You will be a leader that helps to enforce the highest standards around respect for privacy and ethical boundaries, and you will be hugely impactful, writing algorithms that will potentially touch the lives of millions of patients within the Providence healthcare system alone.

Required qualifications for this position include:

1. PhD required in machine learning, or related discipline
2. Publications at top-tier peer-reviewed conferences or journals
3. Proven track record of innovation in creating novel algorithms and advancing the state of the art in computer vision and deep learning.
4. Ability to develop practical solutions to complex problems
5. Able to effectively communicate with engineering and business leaders
6. Proficiency in Python

Preferred qualifications for this position include:

1. Depth and breadth in state-of-the-art recommender systems
2. Solid background in NLP/NLU also helpful
3. Experience working closely with an engineering team to put systems into production
4. Background and experience in distributed systems and the problems that arise when employing ML at scale

Please apply to [e-mail] or ask him any questions.