02 oct
|
Carbon Robotics
|
España
02 oct
Carbon Robotics
España
Deep Learning Quality Specialist
As a Deep Learning Quality Specialist at Carbon Robotics, you will be responsible for maintaining our expanding dataset of high‑resolution images that feed our computer vision algorithms. You will develop a deep understanding of our data annotation practices and assist in diagnosing and fixing complex deep learning models to ensure our products are robust and reliable. You will also help the Deep Learning team by performing field tests and identifying issues with models, often going to the farm to ensure reliable and safe products.
What You’ll Do
Audit data to ensure clean and appropriate datasets
Review imagery, correct labels and classifications, and provide feedback to labelers
Work closely with support to investigate issues and determine what is needed to ensure data integrity
Review data irregularities detected by automated tooling
Validate solutions, document results, and confirm customer feedback
Translate field test results and model issues into actionable insights
Prepare cases for field personnel to review labels and predictions
Help the Deep Learning team prioritize tasks based on impact to customer satisfaction
Knowledge, Skills, and Abilities for Success
Education or professional experience in Agronomy or Farming
Data annotation experience
Highly motivated, independent thinker with strong problem‑solving skills
Highly organized with excellent time management to juggle multiple priorities simultaneously
Collaboration skills to work with customers and internal teams simultaneously
High level of attention to detail and strategic thinking ability
Detail-oriented with proven ability to deliver accurate reporting
Intermediate to advanced Google Suite and Confluence skills desired
Ability to identify and address high‑risk situations and make safe independent decisions based on process
Travel required – 10–15%
Compensation and Benefits
Competitive salaries (USD 72,000–80,000 base, with opportunities based on experience and
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