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Mercor

Software Engineer, Frontier Data Products

San Francisco or NYC$130k–$500kfulltimemidAdded 1 month ago

About this role

Mercor is seeking a Backend Engineer for its Marketplace team to develop key systems for talent and job matching. This role involves creating efficient backend services that directly impact the marketplace's operational performance and business outcomes.

What you'll do

  • Build backend services for candidate-job matching and workflows
  • Create APIs for search, eligibility, and allocation
  • Develop data models for a dynamic labor marketplace
  • Design infrastructure for real-time decision-making
  • Enhance reliability and performance of system workflows
  • Translate product requirements into technical solutions

What they're looking for

  • Experience in building reliable backend systems
  • System design and data modeling expertise
  • High-throughput APIs and distributed systems knowledge
  • Ability to create clean technical systems from product needs
  • Strong engineering standards
  • Familiarity with search and recommendation systems
  • Event-driven architecture experience
  • Knowledge of observability tooling

Benefits

  • Bi-annual performance bonuses
  • Equity grants vested over 4 years
  • Up to $15k relocation bonus
  • $10K housing bonus for proximity to office
  • $1.5K monthly meal stipend
  • Free Equinox membership
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Mercor

Mercor builds a marketplace platform connecting expert talent to AI opportunities, supported by identity infrastructure, matching algorithms, and internal tools for data management. The company is hiring Software Engineers, Machine Learning Engineers, Fullstack Engineers, and Security Engineers to develop backend systems, ML models, cloud infrastructure, and distributed platforms.

Website
mercor.io
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Likely interview questions

  • Walk us through a distributed system you've built that had to handle long-running, stateful jobs. How did you approach idempotency and failure recovery?
  • Tell us about a time you had to design service boundaries for a complex workflow. What principles guided your decisions, and what would you do differently?