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Mercor

Automates candidate screening and matching

Software Engineer - Applied AI, Frontier Engineering

Backend EngineeringUpdated on Nov 14
Full-timeNew York, NY, USA$160k - $500k /yr

About the Job

Requirements

  • Strong backend engineering fundamentals in a modern programming language.
  • Experience with model training and inference.
  • Strong grounding in statistical analysis and experimental design for measuring model performance and improvements.
  • Familiarity with evaluation methods for large language models.

Responsibilities

  • Partner closely with frontier AI labs to understand their data, post-training, and evaluation needs.
  • Build and operate scalable data pipelines for post-training workflows and model evaluations.
  • Design and build scalable systems for synthetic data generation and data quality, and work directly with customers to understand requirements and develop technical solutions.
  • Prototype new data types, benchmarks, and evaluation frameworks.
  • Lead technical discussions with customers.
  • Own projects end-to-end, spanning requirements gathering, creating data creation pipelines, and improving model-adjacent infrastructure.
  • Prototype quickly with researchers and customers, and take systems from early experiments to reliable, scalable production.

Desired Qualifications

  • Comfort working through ambiguity and shipping iteratively.
  • Enjoys ownership and customer-facing problem solving.
  • Thinks entrepreneurially and moves quickly.
  • Balances speed with engineering rigor.
  • Communicates clearly with technical and non-technical users.

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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