Description

VP Machine Learning for Medical Device 

Location: Seattle, WA area – local preferred

Compensation:  $170,000 - $200,000

Citizen or Green Card Holder

Our client, a late-stage Ultrasound medical device start-up, has developed the world’s first technology to instantly and accurately diagnose middle ear infections in children and adults, both presence and (more importantly) types of infection.

They are a team of makers, entrepreneurs, engineers, businesspeople, and scientists with deep technical expertise who love the challenge of reinventing old technologies and creating highly effective new ones, especially medical devices.  They value team play and support of team members, while celebrating individual effort and success. At this late stage of the company, there is the chance to contribute in substantial ways and benefit from a technology that will make a real difference and improve patient outcomes while dramatically reducing the cost of care. 

The client is offering salary, equity and other benefits.  

Qualified candidates are encouraged to submit a current resume to Karen@Peopleconnectstaffing.com.  No C2C or sponsorship is available.

Requirements

• 5 or more years of hands-on job experience working with Machine Learning and deep understanding of mathematics; specifically, experience using Python, Matlab, and virtual machines.
• Experience with Ultrasound highly desired
• Familiarity and experience using machine learning techniques and tools to predict discrete diagnostic outputs from a set of inputs pared down from a large array of inputs.
• Experience with computer engineering principles necessary for handling large data sets for the purpose of determining the optimal sets of data set inputs in complex ML models.
• A sound background in mathematics and statistics necessary for understanding the underlying principles of how machine learning models are formed and understanding their strengths and limitations.
• Able to solve problems and arrive at optimized ML models using methodical documentation and management processes to make efficient use of resources.
• Better than basic understanding of diagnostic endpoints and measures necessary for medical device regulatory clearance.
• A very high degree of scientific curiosity and the ability to infuse that enthusiasm in solving complex problems.
• Able to attend at minimum monthly or as needed meetings onsite.
• Bachelor's degree in Mathematics, Computer Science or related field; Master’s degree or equivalent with on job experience.