VP of AI Engineering
Posted on 7/19/2023
INACTIVE
Cognite

501-1,000 employees

Cognite Data Fusion contextually enriches IT and OT data.
Company Overview
Cognite is on a mission to power a high-tech, sustainable, and profitable industrial future.
AI & Machine Learning
Industrial & Manufacturing
Energy

Company Stage

Private

Total Funding

$340.2M

Founded

2016

Headquarters

, Norway

Growth & Insights
Headcount

6 month growth

-5%

1 year growth

-9%

2 year growth

-3%
Locations
Austin, TX, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Computer Vision
Kubernetes
CategoriesNew
AI & Machine Learning
Requirements
  • You understand the overall architecture of Transformer models, and Generative AI including LLMs
  • You understand the overall software architecture, including cloud software, device software, Kubernetes container orchestration, and modern software design patterns
  • You are familiar with modern techniques for Language Understanding, Computer Vision, and other Machine Learning and AI technologies
  • You're excited about working on a local and global team of engineers, researchers, program managers, and product managers
  • A Masters degree in Computer Science, Electrical Engineering or related fields with focus on software engineering
  • 20+ years of industry experience in Software Engineering, Artificial Intelligence and Machine Learning
Responsibilities
  • The VP of Applied AI Engineering will work closely and collaboratively across Product Management, Product Engineering, and Technical Program Management to develop and focus on adding Generative AI and Machine Learning different layers of Cognite Data Fusion Platform that can lock step with the evolution of the best of breed AI technology. This will allow us to continue our leadership in the Industrial Data Cloud domain, and to build best in class capabilities and product experiences that are delightful to use and to operate
  • To lock-step with the evolution of the best of breed AI technology and human ingenuity, the system will enable the AI model to learn from SMEs, and will have the flexibility to utilize LLMs and State of The Art as the AI technology advances
  • This leader will build an efficient engineering system and team by attracting world-class AI architecture and engineering talent and by utilizing engineering best practices to deliver solid quality software, and fast