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Mercor, based in San Francisco, is seeking a Software Engineer to join their Marketplace team. The role involves building and maintaining backend systems for candidate-job matching and various marketplace workflows. You will focus on high-performance APIs and data models central to AI advancements.
The ideal candidate will demonstrate prowess in backend development and system design, eager to contribute to a high-impact environment. This position includes generous benefits and engages directly with AI projects at a forward-thinking company.
Mercor's mission is to organize human intelligence to power the AI economy. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development. Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $3 million a day.
Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.
As a Software Engineer on the Marketplace team, you will own the core systems that bring human intelligence to AI opportunities You'll work on search, matching, allocation, and workflow infrastructure at the heart of the marketplace, where systems deliver the world’s top experts to staff our cutting edge projects.
The problems are technically demanding and tightly coupled to business outcomes: latency, reliability, throughput, and system quality all directly affect marketplace performance.
This role sits on a core decision layer of the product. Your work will directly shape how the marketplace operates: which opportunities get filled, how quickly hiring happens, and how reliably the system scales as volume and complexity increase.
Python, Go, Kafka, Postgres, Redis, Elasticsearch, Kubernetes, Terraform