The opportunity
The Platform Analytics team builds the systems OpenAI researchers use to understand the quality and behavior of the models we train including what models are doing, why they behave in a particular way, and how that behavior changes across experiments.
What you'll do
Own critical systems across architecture, implementation, integrations,: deployment, monitoring, adoption, and whatever else is required to make them useful.
Design, build, and operate the ingestion, storage, retrieval, and query: systems behind research analytics at OpenAI.
Build platforms for analyzing both structured metrics and unstructured: research data, including samples, traces, evaluation results, and model-behavior data.
Reason below typical service abstractions about algorithms, data structures,: concurrency, storage layout, distributed systems, query performance, and failure modes.
Make architectural tradeoffs across ingestion-time processing, data models,: storage formats, indexing, query execution, caching, and visualization performance.
Work directly with researchers to understand what they are trying to learn,: ask the right questions, and challenge a requested solution when a simpler or more effective approach exists.
What they're looking for
- Recognize when several teams are solving the same problem and turn those: patterns into shared infrastructure, APIs, platform components, or agent-driven workflows.
- Write code, investigate production issues, make realistic estimates, guide: other engineers, and think through testing, rollout, observability, and rollback.
- Keep solutions as simple as the problem allows. Introduce complexity only: when correctness, scale, latency, or reliability genuinely require it, and address the largest bottleneck first.
- Have owned a critical distributed system or research platform end to end and: can explain how you took it from an ambiguous problem to reliable production adoption.
