Tech Stack

Description

You will join the Label Capture team to create digital twins of complex labels and identification documents, evolving the product by adding features and optimizing performance. You'll work on computer vision and deep learning algorithms to improve information extraction from printed documents, driving end-to-end quality improvements and mentoring team members.

Requirements

• 5+ years of industry experience solving recognition problems with launched products
• Fluency in C++ and Python
• Experience running ML models on mobile devices
• Experience with ML frameworks (PyTorch, Jax, TensorFlow)
• Skilled in software design, problem-solving, and debugging

Responsibilities

• Drive and solve semantic document parsing for customer use cases
• Handle all phases of end-to-end quality improvements (metrics, prototyping, testing, integration, model creation, data collection, analysis, debugging)
• Stay current with latest research in document classification, text recognition, and information extraction
• Set direction and identify opportunities to push boundaries of recognition
• Mentor team members on code quality and engineering practices