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Data Annotation Manager / QC
ProntoSan Francisco, United Statesfull_timeVerifiedPosted 29 Apr 2024
About the role
While most Autonomous Vehicle (AV) technology companies are stuck in R&D mode, Pronto is a world-leader in commercializing AV tech via our Autonomous Haulage System, which is automating haulage operations at mines and quarries around the world. Pronto’s team of Silicon Valley veterans has been at the forefront of every major AV development over the past 20 years, with a relentless focus on commercializing the technology, leading to our current specialization in off-road applications. This focus and our decades of experience have put Pronto on a track to become the world’s first profitable AV technology company.
Pronto is looking for a data specialist to run the data QC and labeling pipeline for our machine learning team.
We’re an equal opportunity employer and do not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
Pronto is looking for a data specialist to run the data QC and labeling pipeline for our machine learning team.
Responsibilities
- Perform quality control and labeling for images used for machine learning (ML) models
- Manage a large team of remote labelers
- Upload prioritized image data for labeling
- Create and track metrics for labelers
- Iterate on existing labeling guidelines for multiple types of computer vision tasks
- Identify common errors in labeling
- Communicate feedback and priorities to the labeling team
- Work directly with the ML team
Requirements
- Prior experience labeling or performing quality control for ML training data
- Detail-oriented approach
- Excellent communication skills
- Effective collaboration with members of the team
- Familiarity with command-line interface tools preferred
- Knowledge of labeling policies for multiple types of computer vision tasks preferred
We’re an equal opportunity employer and do not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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