Machine Learning / Data Scientist
Confirmed live in the last 24 hours
Docugami

11-50 employees

Docugami provides AI document engineering.
Company Overview
Docugami's mission is to transform how businesses create and execute critical business documents. Applying breakthrough artificial intelligence to unstructured and semi-structured information, Docugami enables organizations to radically improve productivity, compliance and insight.
AI & Machine Learning

Company Stage

Pre-seed

Total Funding

$12.9M

Founded

2017

Headquarters

Kirkland, Washington

Growth & Insights
Headcount

6 month growth

0%

1 year growth

12%

2 year growth

16%
Locations
Kirkland, WA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Natural Language Processing (NLP)
Computer Vision
CategoriesNew
AI & Machine Learning
Data & Analytics
Requirements
  • More than five years of experience after completing PhD, or equivalent demonstrable industry experience
  • PhD (or equivalent experience) in areas like computer science, mathematics, statistics, electrical engineering, or related fields
  • Deep and up-to-date experience with some of the following: natural language processing (NLP), machine translation, self-supervised learning, active learning, computer vision, statistics, causal inference, and other related disciplines
  • Programming skills and familiarity of modern ML frameworks
  • Research track demonstrated by top-level journal and conference publications
  • Strong problem-solving and self management skills
  • Passion for technical and scientific excellence
  • Strong communication skills and capacity to report and disseminate results
Responsibilities
  • You love solving really challenging problems
  • You seek opportunities to see your research deployed in practice to solve real world problems and impact millions of users
  • You enjoy working at the very cutting edge of R&D
  • You want to experience an early stage startup
  • Proposing solutions to the different science problems in an evolving environment
  • Collaborating with engineering and product leadership to plan and prioritize a long-term roadmap of science breakthroughs
  • Working with the engineering team who will be responsible for integrating and deploying your work in production
  • Conducting regular internal science reviews and educational sessions for the team
  • Working with our partners in academia to stay at the very forefront of R&D in our space