Job description
Virta Health is on a mission to transform diabetes care and reverse the type 2 diabetes epidemic. Current treatment approaches aren’t working—over half of US adults have either type 2 diabetes or prediabetes. Virta is changing this by helping people reverse type 2 diabetes through innovations in technology, personalized nutrition, and virtual care delivery reinvented from the ground up. We have raised over $350 million from top-tier investors, and partner with the largest health plans, employers, and government organizations to help their employees and members restore their health and live diabetes-free. Join us on our mission to reverse diabetes in 100M people by 2025.
As a full stack health care company of physicians, engineers, marketers and more under one roof, Virta collects comprehensive data on our patients’ experience. The Applied AI team leverages this data to build the next generation of health care for chronic diseases. As a member of this team, you will build and interpret intelligent systems that power our product in order to scale the treatment, drive patient acquisition, and improve patient outcomes.
Responsibilities
Applied AI Products: Research, develop, deploy, and monitor intelligent systems to improve patient acquisition and outcomes at scale
Reframe vague but mission-critical business objectives into empirical problems that can be addressed with machine learning, optimization routines, and statistical modeling
Conduct exploratory analyses of users and business processes to understand your datasets and make excellent modeling choices downstream
Leverage our platform/tooling to develop and deploy models in our production environment
Understand the impact of your models on user and business level KPIs; leverage this understanding to guide subsequent efforts
Applied AI Platform: Collaborate with other machine learning engineers in designing extensible software and infrastructure to accelerate model training, serving, and operations
Product Leadership: Participate in setting the direction of highly cross functional teams (incl. Applied AI, Product Engineering, Design, Clinical Ops, and Marketing)
90 day plan
Within your first 90 days at Virta, we expect you will do the following:
Immerse yourself in the rich data we collect in service of our patients’ care. Our data includes high dimensional time series data, meal images, natural language discourse, insurance claims, and much more
Ship one new data pipeline or ML model as a feature in our patient or clinician-facing products
Teach and inspire other Applied AI team members on your areas of expertise through knowledge sharing, pair programming, and code reviews
Must-Haves
You have 4+ years experience as a machine learning engineer or scientist, deploying models in production at scale. Experience deploying models as a part of a (possibly stateful) microservice is strongly desired.
You are passionate about directly optimizing core products or operations through AI/ML systems deployed to production
You care deeply about exploring data and understanding the real life user behavior and processes that generate it
You are expert in Python’s open source machine learning ecosystem. Experience with tensorflow or pytorch is strongly desired.
You are strong with SQL and able to extract data from data warehouses like Redshift or Bigquery. Experience with modern data processing technologies like Apache Spark or Apache Beam is a plus
You excel at communicating progress, trade-offs, and the results of your work to team members from other functions
Values-driven culture
Virta’s company values drive our culture, so you’ll do well if:
You put people first and take care of yourself, your peers, and our patients equally
You have a strong sense of ownership and take initiative while empowering others to do the same
You prioritize positive impact over busy work
You have no ego and understand that everyone has something to bring to the table regardless of experience
You appreciate transparency and promote trust and empowerment through open access of information
You are evidence-based and prioritize data and science over seniority or dogma
You take risks and rapidly iterate
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