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Mercor

Automates candidate screening and matching

Product Manager - Environments

Technical Product ManagementPosted on Nov 11
Full-timeSan Francisco, CA, USA$180k - $300k /yr

About the Job

Requirements

  • Have at least 3 years of experience as a product manager.
  • Be comfortable building scrappy minimum viable products when needed to validate direction, unblock engineering, or accelerate iteration.
  • Be able to connect user needs and business context to long-term product direction.
  • Conduct user research and customer interviews effectively.
  • Be comfortable running rigorous experiments and advancing visionary product bets.

Responsibilities

  • Work with researchers at frontier labs to identify where agents fall short and translate those gaps into requirements for worlds, tasks, and verifiers.
  • Build task-generation systems that turn a single world into thousands of realistic, difficult, verifiable tasks, with controls for teams to steer what is produced.
  • Set standards for world readiness and for tasks to be difficult, solvable, and fairly graded, and build checks to ensure each project meets those standards.
  • Build feedback loops that show how each run performs so teams can identify bottlenecks and improve yield and difficulty with each iteration.
  • Turn successful project work into a shared platform, including tools experts use to review and improve tasks, so each new environment is faster to build.
  • Define success using high-quality tasks delivered, balance throughput, difficulty, and cost, and use lab feedback and agent failures to guide future platform development.

Desired Qualifications

  • Prior experience in software engineering, machine learning, or data science.

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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