ML / AI Engineer
Posted on 3/9/2023
INACTIVE
Notable

201-500 employees

Healthcare administration automation tools
Company Overview
Notable's mission is to make healthcare more accessible, affordable, efficient and compassionate. Notable uses intelligent automation to eliminate the massive administrative burden that threatens the future of healthcare.
AI & Machine Learning
B2B

Company Stage

Series B

Total Funding

$126.5M

Founded

2017

Headquarters

San Mateo, California

Growth & Insights
Headcount

6 month growth

0%

1 year growth

23%

2 year growth

81%
Locations
Burlingame, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python
Tensorflow
Pytorch
Pandas
NumPy
CategoriesNew
AI & Machine Learning
Requirements
  • Demonstrated ability to translate business requirements and metrics into machine learning model specifications
  • Quickly prototype new models from open-sourced code and demonstrate results
  • Ability to design and train new model architectures for complex data
  • Experience working with real-world data: large, messy, incomplete, irregular, etc
  • Experience working with a mix of structured and unstructured data
  • Proficiency with Python and the standard ML stack (numpy, pandas, scikit-learn)
  • Experience with a deep learning package, e.g. Tensorflow, PyTorch
  • Experience deploying ML models in production
Responsibilities
  • Work with the product development team and product managers to define scope of work, timeline and product specifications
  • Work with backend engineers to deploy, maintain and scale AI models
  • Define interfaces between the microservices that runs and delivers AI models
  • Discover, collect, clean and transfer data to train AI models
  • Experimentation of different AI models, methodologies, frameworks and communicate critical evaluation metrics to product teams
  • Explore, refine, improve best practices within the ML team
  • Push the boundaries of ML and AI and innovate on how to best leverage existing technologies to solve new problems