Deep Learning Field Engineer
Confirmed live in the last 24 hours
Matroid

11-50 employees

Software Development
Company Overview
Matroid makes computer vision simple by providing an easy-to-use, intuitive Studio for creating and deploying Detectors (computer vision models) to search video for actions, objects, and events with no additional programming required. Matroid can monitor any live stream or search recorded video, providing real-time notifications when events of interest have been detected. Matroid reduces operating costs associated with manually searching through video footage for an object or a specific person, and increases efficiency, safety, and regulatory compliance.
AI & Machine Learning

Company Stage

Series B

Total Funding

$37M

Founded

2016

Headquarters

Palo Alto, California

Growth & Insights
Headcount

6 month growth

-16%

1 year growth

-10%

2 year growth

8%
Locations
Palo Alto, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Tensorflow
Pytorch
CategoriesNew
AI & Machine Learning
Deep Learning
Computer Vision
Requirements
  • Bachelor's degree in computer science, computer engineering, electrical engineering, or another technical field.
  • Experience training and deploying state-of-the-art CV models using popular machine learning frameworks, such as TensorFlow or PyTorch.
  • Strong software engineering skills.
  • Solid oral, written, presentation, collaboration, and interpersonal communication skills.
  • Adept at communicating to both technical and commercial audiences.
  • Willingness and eligibility for security clearance up to TS/SCI.
Responsibilities
  • Train state-of-the-art CV models across a broad range of domains, such as object detection, anomaly detection, panoptic segmentation, action recognition, and tracking.
  • Deploy end-to-end CV systems across a range of environments (cloud, edge, hybrid).
  • Integrate Matroid into inspection workflows and third-party systems, such as manufacturing execution systems, safety alert systems, and video management systems.
  • Perform quantitative and qualitative evaluation of the CV system and iterate on it to meet performance requirements.
  • Act as the technical expert, advising on all matters from technical scoping of engagements, to model training and deployment.
  • Empower customers with CV by designing and leading product training sessions.