SuperAnnotate

SuperAnnotate

Global Account Director

San Francisco · Director · Full-time

Sponsorship not specified$350k-$450kDetected 27 days ago
DatabricksMachine LearningSalesAccount ManagementOutbound SalesExcel

About the role

  • Our global network of expert specialists, scalable managed operations, precise talent matching, and full project transparency ensure unmatched data quality at scale.
  • You will be working directly with the sales management and founding team daily, and be expected to have a critical impact on the organization and on its revenue.

Responsibilities

  • Strong ability to succeed in multi-channel pipeline generation including inbound discovery calls, outbound prospecting, working with SDRs and working with partners

Requirements

  • 5+ years of experience selling and generating demand for enterprise services, with strong preference for candidates who have sold data services, managed services, or professional services into AI/ML buyers
  • Previous experience selling into AI/ML, data labeling, data annotation, RLHF, or related human-data services required
  • Experience with MEDDICC and enterprise selling methodologies such as Command of the Message

Skills

  • This is a full-time, hybrid position based in San Francisco.

Compensation

  • $350k-$450k

Company info

  • Ability to travel occasionally to meet customers and attend industry events

Equal opportunity

  • We are an equal-opportunity employer and value diversity at our company.
  • At SuperAnnotate diversity means to us making an effort to reflect the many experiences and identities of the outside world, and treating each other with fairness and without bias.
  • Every day we foster an environment where people of all backgrounds not only belong, but excel to succeed as a company and grow together.
  • We offer equal opportunity regardless of sex, sexual orientation, national origin, color, race, age, marital status, disability, gender identity, veterans and more.

This listing is sourced directly from SuperAnnotate's careers page and normalized into a canonical job model.