8 days ago
Base Salary
$130k - $500k/yr
Responsibilities
- Build and operate backend services for candidate-job matching, routing, allocation, and marketplace workflows.
- Develop APIs and internal systems for search, eligibility, scoring, allocation, and fulfillment.
- Design data models and abstractions for a rapidly evolving labor marketplace.
- Build real-time and asynchronous decisioning infrastructure operating at high volume.
- Develop workflow engines for onboarding, vetting, routing, and placement.
- Improve the performance, reliability, observability, and evolvability of product-critical marketplace systems.
Requirements
- Track record of building and operating reliable backend systems in production.
- Strong judgment in system design, performance, reliability, and data modeling.
- Experience or comfort with high-throughput APIs, distributed systems, and asynchronous workflows.
- Ability to translate product and marketplace requirements into clean technical systems.
- High engineering standards and a preference for simple, durable abstractions.
- Preferred experience with search, recommendation, matching, scheduling, or marketplace systems.
- Preferred experience supporting ML-powered products or integrating model inference into production systems.
- Preferred familiarity with event-driven architecture, queues, caching, and observability tooling.
Benefits
- Bi-annual performance bonus structure and equity grant.
- Relocation, housing, meal, laundry, and personal wellness support.
- Free Equinox membership.
- Health, dental, and vision insurance.
- In-person work five days per week in the San Francisco, New York City, or London office.
Tech Stack
Categories
About Mercor
We find the best experts in every professional domain and put their knowledge to work training frontier models. Through APEX, we measure whether those models can actually perform economically valuable work. We're also bringing that expertise to enterprises: deploying custom AI agents, staffing teams with vetted domain experts, and helping organizations encode their own knowledge into AI systems.