Labeling Operations Manager

Stack AV Logo

Stack AV

πŸ“Remote - United States, Worldwide

Summary

Join Stack's Labeling Operations team as the Labeling Operations Manager! You will lead an internal team and external vendors in delivering high-quality sensor data labels for the development of our self-driving system. Collaborate with Product and Engineering teams to improve labeling and QA processes. This critical role requires managing workflows, vendor relationships, and data analysis to optimize operations. You'll ensure the continuous delivery of high-volume, quality labels meeting customer needs. Success in this position demands strong leadership, data analysis skills, and experience in data annotation or related fields.

Requirements

  • 10+ years of Operations Management or related experience
  • Significant experience leading teams responsible for data annotation or related functions
  • Demonstrated experience managing globally distributed workforce vendors
  • Proven ability to define and implement complex operational workflows that are heavily data driven
  • Strong data analysis skills including experience building and reporting on meaningful business metrics

Responsibilities

  • Manage the Labeling Operations team in the Product Development organization
  • Collaborate with key customers across the organization to define and continually refine labeling ontology and policy
  • Ensure efficient workflows and policies are in place that result in the delivery of a high volume of quality labels meeting customer needs on a continuous basis
  • Oversee all aspects vendor relationships and partner organizations responsible for ground truth labeling of AV sensor data, including training, and policy
  • Utilize data and analysis to identify opportunities for improvement in operational workflows and processes

Preferred Qualifications

  • Prior experience working in an AV or Robotics company is strongly preferred
  • General understanding of ML training of Perception models and associated inputs (e.g. calibration), data infrastructure, and visualization tooling preferred

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