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Mercor

Automates candidate screening and matching

Engagement Manager

Account Executive +1Updated on Nov 14
Full-timeSan Francisco, CA, USA$180k - $200k /yr

About the Job

Requirements

  • At least 4 years of total work experience, including experience in consulting or a technical program management role in industry.
  • A technical bachelor's or master's degree, or equivalent practical experience.
  • Experience at a top-tier consulting firm and a fast-growth technology startup.
  • A proven track record in enterprise client-facing roles and expanding customer relationships.
  • Ability to understand the machine learning training and evaluation lifecycle and build trusted relationships with technical customers.

Responsibilities

  • Manage and grow a portfolio of relationships across application-layer companies, research labs, and enterprise customers.
  • Serve as the primary point of contact for customer questions, issues, and escalations; triage internally and drive resolution.
  • Lead commercial processes to close new and existing business.
  • Manage technical relationships with research teams and help guide evaluation and training strategy.
  • Work cross-functionally with product, operations, and engineering to track delivery and timelines.
  • Forecast revenue growth and help leadership understand how to unblock additional growth opportunities.

Desired Qualifications

  • Experience at a top-tier consulting firm and a fast-growth technology startup.
  • A technical bachelor's or master's degree, or equivalent practical experience.

About the Company

Mercor

Automates candidate screening and matching

Mercor provides an AI-driven recruitment platform that automates key parts of hiring for both job seekers and employers. Job seekers upload their CVs and complete a 20-minute AI-led video interview, after which a proprietary language model generates detailed candidate profiles; employers receive automated resume screening, candidate matching, and initial interviews, with tailored AI interviews for specialized roles. The system uses a company-trained model to rank and recommend candidates by qualifications and predicted performance, and operates on a finder’s-fee revenue model with large-scale usage across software, operations, design, and other fields, including AI labs. Its goal is to speed up hiring while reducing bias and delivering better job-to-citizen matches.

Company size
201-500
Company stage
Series D
Total funding
$1.2B
Headquarters
Menlo Park, CA
Founded
2023

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