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Machine Learning Support Engineer - Remote

Posted 15 weeks ago
Customer Service
Full Time
India

Overview

As a Machine Learning Support Engineer at Labelbox, you will be the frontline of customer support, utilizing live chat and internal resources to resolve product issues and provide proactive guidance to customers.

In Short

  • Create great experiences for customers needing help.
  • Build trust and advisory relationships with customers.
  • Learn Labelbox's product deeply and assist customers.
  • Understand customer success definitions and help them achieve it.
  • Propose creative solutions to customer business problems.
  • Represent customer needs in internal discussions.
  • Monitor trends in customer experiences.
  • Work with teams to provide customers with necessary tools.

Requirements

  • 2+ years experience in a Technical Support team.
  • BA/BS in Computer Science/Engineering.
  • 2+ years of technical expertise in Python.
  • Experience with Machine Learning is a plus.
  • Ability to navigate complex customer requests.
  • Empathy, patience, and strong people skills.
  • Quick learner of new technologies.
  • Outstanding organizational skills and multitasking ability.
  • Creative problem solver.
  • Experience with support software like Intercom, GitHub, Jira.

Benefits

  • Remote-friendly hybrid model.
  • Focus on collaboration and connection.
  • Asynchronous communication encouraged.
  • Autonomy and ownership of tasks.
  • Convenience of hub-based gatherings.
Labelbox logo

Labelbox

Labelbox is a leading provider of high-quality training data for generative AI, offering a comprehensive platform that combines on-demand labeling services with an industry-leading data labeling platform. Their Boost labeling service leverages a community of highly-educated experts to rapidly generate data for various AI applications. Backed by prominent investors such as SoftBank and Andreessen Horowitz, Labelbox serves Fortune 500 enterprises and top AI labs, ensuring unmatched control and transparency in the data labeling process. The company embraces a hybrid work model, fostering collaboration while supporting remote work.

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