Machine Learning Engineer
Posted on 7/19/2023
INACTIVE
HEALTH[at]SCALE

11-50 employees

ML precision delivery healthcare company
Company Overview
HEALTH[at]SCALE is on a mission to usher in a new era of care that is proactive, personalized, and precise. HEALTH[at]SCALE is a healthcare machine intelligence company that uses proprietary advances in artificial intelligence and machine learning to optimize care delivery for individuals by empowering at-risk payers, employers and providers.
AI & Machine Learning
Cybersecurity
Social Impact
Financial Services
Consumer Goods
Data & Analytics

Company Stage

Series A

Total Funding

$16M

Founded

2015

Headquarters

San Jose, California

Growth & Insights
Headcount

6 month growth

-6%

1 year growth

-6%

2 year growth

38%
Locations
San Francisco, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python
Data Science
Data Structures & Algorithms
Java
CategoriesNew
AI & Machine Learning
Software Engineering
Requirements
  • BS, MS or PhD in Computer Science or related technical field
  • 2+ years of experience with machine learning and data science in academia or industry
  • Strong understanding of the foundational concepts of machine learning and artificial intelligence
  • Strong proficiency in Python (preferred), Java or C/C++
  • Experience in cloud computing, parallel/distributed computing and workflow management
  • Excellent communication skills
Responsibilities
  • Design, engineer, test, deploy and maintain machine intelligence platforms and applications for real-world production use at scale
  • Improve the accuracy, runtime, scalability and reliability of machine intelligence algorithms and software
  • Develop and implement machine intelligence platform APIs for multiple use-cases
  • Drive architecture of platform and application capabilities embedding machine intelligence
  • Collaborate with machine learning scientists and data scientists to develop prototyped solutions and translate leading-edge ideas into production-ready systems
  • Work with data engineers to ensure seamless interactions between data pipelines and machine learning pipelines in development and production environments