Backend Engineer, Marketplace

Mercor•San Francisco, CA

5d•Onsite

About The Position

As a Backend Engineer on the Marketplace team, you will build the core systems that govern how talent and opportunities meet on Mercor. You’ll work on search, matching, allocation, and workflow infrastructure at the heart of the marketplace, where system quality directly affects fill rate, hiring speed, and revenue. The problems are technically demanding and tightly coupled to business outcomes: latency, reliability, throughput, and system quality all directly affect marketplace performance.

Requirements

Track record of building and operating reliable backend systems in production
Strong judgment in system design, performance, reliability, and data modeling
Comfort working on high-throughput APIs, distributed systems, and asynchronous workflows
Ability to translate product and marketplace requirements into clean technical systems
High engineering standards and a bias toward simple, durable abstractions

Nice To Haves

Experience with search, recommendation, matching, scheduling, or marketplace systems
Experience supporting ML-powered products or integrating model inference into production systems
Familiarity with event-driven architecture, queues, caching, and observability tooling

Responsibilities

Backend services that power candidate-job matching, routing, and marketplace workflows
APIs and internal systems for search, eligibility, scoring, allocation, and fulfillment
Data models and system abstractions for a rapidly evolving labor marketplace
Infrastructure for real-time and asynchronous decisioning at high volume
Operational systems and tooling that keep product-critical workflows reliable, observable, and easy to evolve
Build the systems that determine which candidates are eligible for which opportunities
Design matching and allocation infrastructure that balances speed, quality, and fill rate
Improve the performance and reliability of APIs serving marketplace decisions in real time
Develop workflow engines for onboarding, vetting, routing, and placement
Design backend abstractions that let product and ML teams iterate quickly without degrading system quality