Software Engineer, Implicit Signals

About this role

About the Team

Our team builds classification and evaluation systems that give post-training and research teams fast, reliable feedback on model behavior. We combine machine learning and production engineering to make these capabilities accurate, efficient, and useful at scale, helping researchers assess changes and improve models and products.

We work closely with researchers and data scientists and have broad ownership of the software that makes these capabilities available. Our work spans real-time systems, data engineering, model serving, and tools for experimentation, with careful attention to performance, reliability, and privacy.

About the Role

We’re looking for a software engineer to build and evolve our classification and evaluation platform. You’ll develop services, online and offline pipelines, and tools that help researchers and data scientists turn an idea into a working measurement and iterate on it quickly.

This role combines software and data engineering with hands-on production ownership. You’ll shape the architecture, deliver new capabilities, improve inference efficiency, and keep the system dependable as workloads and requirements evolve. Strong candidates will bring deep software engineering expertise and an interest in building a technical product in close partnership with its users.

In this role, you will:

• Design and build software services and APIs for configuring, running, and managing classifiers and evaluations.

• Build and operate online and offline classification pipelines that support reliable, efficient execution at scale.

• Improve model-serving performance, including throughput, latency, concurrency, and compute utilization.

• Build tools that make experimentation, debugging, and iteration straightforward for researchers and data scientists.

• Own production reliability, observability, and incident response, and reduce the operational burden of running the platform.