Mercor
Software Engineer, Frontier Data Products
About this role
Build production orchestration systems that coordinate human experts and AI models through multi-stage, long-running workflows for frontier AI companies. This backend role owns the infrastructure capturing, validating, and reconciling expert judgment at scale, where early engineers shape the architecture itself.
What you'll do
- Design distributed state machines and services for workflows spanning automated processing, model inference, and expert review cycles
- Implement orchestration primitives including retries, failure recovery, idempotency, and auditable state transitions for jobs lasting days with partial redo capability
- Integrate model inference into production workflows while maintaining debuggability and human oversight
- Build APIs and operational tooling for product, operations, and ML teams to operate and monitor systems at scale
- Own end-to-end reliability and observability where silent failures corrupt results rather than returning errors
- Debug complex stateful workflows spanning automated steps, model calls, and human reviewers
What they're looking for
- Backend systems design and distributed state machines
- Async workflows, message queues, and event-driven architecture
- Idempotency, retry logic, and failure recovery patterns
- API design and service boundaries
- Observability, monitoring, and debugging complex systems
- Production reliability and operational experience
- Working with non-deterministic systems (humans and models)
- Long-running job orchestration and reconciliation
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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
Likely interview questions
- Tell us about a time you designed a system that had to handle non-deterministic behavior—how did you approach state management and failure recovery?
- How would you handle a situation where a multi-day job needs to be partially re-executed after human review changes an earlier stage's output?