Machine Learning Engineer
Confirmed live in the last 24 hours

51-200 employees

Medical product development platform
Company Overview
Machinify is on a mission to ensure that patients get the right treatment, at the right time, at the right price. The cloud-based Machinify AI platform delivers products that are transforming healthcare administration from a human-powered, error-prone series of workflows fueled by faxes and spreadsheets to a world of transparent, realtime care and payment decisions.
Palo Alto, CA, USA
Experience Level
Desired Skills
Data Structures & Algorithms
AI & Machine Learning
  • You enjoy solving real-world business problems by developing, from scratch, ML models and deploying them in production - and have been doing that successfully for a while
  • You are comfortable measuring and optimizing the direct business impact of your work
  • You are interested in learning about the healthcare industry and helping us improve the care millions of people receive
  • You are scrappy, and love solving hard problems that matter
  • You are experienced with SQL, handling large-scale data, and are comfortable with at least one programming language (Python, R, etc.)
  • You have experience building ML models using modern ML approaches like Neural Nets or Tree-ensembles from scratch for new applications - making decisions relating to which supervised labels to use, the metric to optimize for, and the features likely to be useful
  • You are a critical thinker who can be strategic without losing attention to detail
  • You are comfortable taking the initiative and owning projects from start to finish
  • You can build positive relationships based on trust and value delivered
  • Advance Machinify's capabilities to model and understand medical decisions which will power a range of products in the claims processing space
  • Make thoughtful decisions around which methods/algorithms are likely to work well in solving the business problem at hand
  • Consider the quality of the available input data and build robust systems that will work well in the presence of noise/errors
  • Measure the model output in practical real-world settings and iterate your approach
  • Learn about the healthcare industry and become an expert over time