Software Engineer, Implicit Signals

This software engineer builds the services, pipelines, and tools researchers use to configure and run classification and evaluation systems. The work combines production software engineering with model-serving performance, reliability, and close collaboration with research and data science teams.
* Permanent* Hybrid### Skills and expertise API design

Distributed systems

Online and offline pipelines

Model serving

Concurrency Caching Performance  optimization

Observability### Key responsibilities
* Build services and APIs for configuring, running, and managing classifiers and evaluations.
* Develop classification pipelines and improve model-serving throughput, latency, concurrency, and compute utilization.
* Own platform reliability and build tools that help researchers experiment, debug, and iterate.## How this job compares

Compared with 1,047 open mid-level engineering jobs on October 10, 2026.Pay:
This job pays $347K to $445K a year. The 452 open mid-level engineering jobs that publish US pay start at $138K on average, so this job starts about 151% higher.

Similar open jobs:
We Love AI Jobs lists 1,047 open mid-level engineering jobs at 274 companies.

Remote work:
This job is hybrid. 104 of the 1,047 mid-level engineering jobs (10%) are remote.

AI in this role:
High. AI is the core of the work: building, training or deploying AI systems. The platform directly runs classification and evaluation systems that measure model behavior and supports model serving. Building and operating these AI-related systems is central to the role.## Full description

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  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.
• Partner with machine learning engineers to bring new classification capabilities into production.
• Work closely with post-training researchers and data scientists to understand their workflows, identify high-impact improvements, and shape the product.

You might thrive in this…