Mercor Logo

Mercor

Software Engineer, Marketplace

Reposted 18 Days Ago
In-Office
San Francisco, CA, USA
Mid level
In-Office
San Francisco, CA, USA
Mid level
Design, build, and operate backend systems for candidate-job matching, routing, scoring, and marketplace workflows. Develop high-throughput APIs, data models, real-time and async decisioning, and observability tools to ensure reliable, low-latency marketplace performance and scalable fulfillment.
The summary above was generated by AI
About Mercor

Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents.

 

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.

About the Role

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.

What You'll Build
  • 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

Example Problems
  • • Build the systems that determine which candidates are eligible for which opportunities

  • • Design matching and allocation infrastructure that balance 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

What We're Looking For
  • • 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 Have
  • • 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

Why This Role

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.

Tech Stack

Python, Go, Kafka, Postgres, Redis, Elasticsearch, Kubernetes, Terraform

Benefits
  • Bi-annual performance bonus structure

  • Generous equity grant vested over 4 years

  • Up to $15k Relocation bonus

  • $10K housing bonus (if you live within 0.5 miles of our office)

  • $1.5K monthly stipend for meals

  • Free Equinox membership

  • $200 monthly laundry reimbursement

  • $200 monthly personal wellness reimbursement

  • Health, Dental, Vision insurance

HQ

Mercor San Francisco, California, USA Office

San Francisco, California , United States, 94105

Similar Jobs

20 Days Ago
Easy Apply
Remote or Hybrid
USA
Easy Apply
180K-265K Annually
Entry level
180K-265K Annually
Entry level
Healthtech • Information Technology • Software • Telehealth
Lead the technical direction of Zocdoc’s patient acquisition platform, building scalable APIs, microservices, AWS infrastructure, and React experiences. Improve SEO, page speed, system reliability, and patient-facing data access. Collaborate with Product, Design, and Marketing, integrate third-party data and Contentful, apply LLM technology, promote engineering excellence, mentor engineers, and drive AI-focused innovation across distributed teams.
Top Skills: APIsAWSCi/CdContentfulLlm SystemsMicroservicesObservabilityReactSeo
14 Days Ago
In-Office
San Francisco, CA, USA
250K-300K Annually
Mid level
250K-300K Annually
Mid level
Artificial Intelligence • Big Data
Build end-to-end product experiences supporting expert acquisition, onboarding, assessment, matching, activation, and retention. Partner with Growth and Operations to identify bottlenecks, instrument funnels, run experiments, and improve measurable outcomes. Develop internal tools and automation, create durable product primitives, and make thoughtful tradeoffs among speed, reliability, and maintainability while working closely with founders and cross-functional teams.
26 Days Ago
In-Office
Mountain View, CA, USA
175K-215K Annually
Mid level
175K-215K Annually
Mid level
Automotive
Build and scale Waymo’s ride-hailing marketplace systems for trip management, vehicle-rider matching, pricing, and vehicle positioning. Develop infrastructure to train and deploy machine learning and optimization models for real-time decisions. Create experimentation, monitoring, and analysis systems for deployed models, and partner with data scientists to productionize pricing and matching models.
Top Skills: Backend Distributed SystemsC++Low-Latency SystemsMachine LearningMl PipelinesOptimization Infrastructure

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account