Performance Quality Technician

Carbon Robotics Carbon Robotics · Robotics · Carbon Robotics, Corporate · Deep Learning

The Performance Quality Technician at Carbon Robotics is responsible for identifying, diagnosing, and resolving systemic issues within the company's high-resolution imagery dataset. This role involves auditing data, conducting field experiments, analyzing customer feedback, and collaborating with engineering and Deep Learning teams to improve system performance and data integrity. The position requires a strong understanding of agricultural practices and data annotation experience.

What you'd actually do

  1. Gain deep understanding of how the system works, and what can cause it to not work optimally
  2. Audit data to ensure clean and appropriate datasets
  3. Work closely with support to help investigate issues and determine what is needed to ensure data integrity
  4. Validate solutions, document results and document customer feedback
  5. Translate field tests and model issues, and analyze customer feedback

Skills

Required

  • Education or professional experience in Agronomy or Farming
  • Strong understanding of agricultural industry practices, operations and culture.
  • Data annotation experience
  • Highly motivated, independent thinker with great problem solving skills
  • Highly organized with excellent time management to juggle multiple priorities at the same time
  • Collaboration skills to work with customers and internal teams simultaneously
  • High level of attention to detail & the ability to think strategically
  • Detail-oriented, with proven ability to deliver accurate reporting
  • Ability to identify and address high risk situations & make safe independent decisions based on process
  • Traveling to farms required - 25-50%

Nice to have

  • Intermediate to advanced Google Suite and Confluence skills desired

What the JD emphasized

  • AI/deep learning
  • computer vision
  • dataset auditing
  • field experiments
  • customer feedback analysis

Other signals

  • AI/deep learning
  • computer vision
  • dataset auditing
  • field experiments
  • customer feedback analysis