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Mercor

Automates candidate screening and matching

Tech Lead – Applied AI - Evals

Engineering LeadershipUpdated on Nov 14
Full-timeSan Francisco, CA, USA$260k - $500k /yr

About the Job

Requirements

  • A Bachelor's degree in Computer Science or a related field is required.
  • At least 5 years of experience building and running backend systems in production, including time at senior or staff level.
  • Strong full-stack skills in a modern backend language such as Python, Go, or TypeScript and a frontend framework such as React.
  • A track record of owning a platform or product area end to end, including leading the team that built it.
  • Strong product sense grounded in user needs.
  • Experience building data-heavy products, including data models, APIs, and views over large volumes of results.
  • Excellent written and verbal communication with engineers, researchers, and customers.
  • Comfort with ambiguity and iterative shipping.

Responsibilities

  • Own the evals product end to end, decide what the team builds next, and remain hands-on in the code.
  • Set the architecture and roadmap and make tradeoff decisions in design reviews.
  • Ship the APIs, data models, and UI used by labs and enterprises to run evaluations and compare models.
  • Build systems to run every new frontier model on APEX and publish accurate, defensible results to the public leaderboard.
  • Build failure analysis that links each failure pattern to the exact steps that went wrong.
  • Calibrate graders against expert judgment and decide when a grader or agent change is ready to ship.
  • Keep the product reliable and compute costs under control.
  • Lead pilots with labs and enterprises and bring customer learning into the roadmap.
  • Hire and mentor engineers and manage the people on the team.

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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