Software Engineer, Model Lifecycle and Signals

About the Role

As a Software Engineer on the Model Lifecycle and Signals team, you'll own the bridge between frontier models and every user-facing product, used at massive scale. You'll decide when to use which model, spot where models go off track and build the guardrails to keep them on it, and shape what the next generation of models should learn.

This role sits at the intersection of infrastructure, data, and product. You'll bring models from preview to production, dig into real-world data to find out what's actually working, and partner with research, inference, product, and data science teams to turn that evidence into better products and better models.

What You'll Work On

• Get new frontier models into users' hands the day they're ready, and retire old ones without disruption.
• Evaluate internal and external preview models before launch and give meaningful feedback to the teams building them.
• Build the model router: decide which model handles each request, balancing quality, speed, and cost at massive scale.
• Build signals and an experimentation platform that show where each model shines, where it goes off track, and what 'better' actually means.

Qualifications

• Track record of shipping production systems people rely on, owning problems end to end, and automating processes.
• Experience building and operating evaluation, measurement, or model serving systems (e.g., AI evals, experimentation, ranking/relevance, or routers).
• Ability to turn ambiguous quality questions into concrete metrics, pipelines, and decisions.
• Fluency with data and experience collaborating effectively with data scientists and researchers.
• Strong curiosity and intuition regarding model and agent behavior.

Interview Process

• 2–3 short technical interview rounds.
• Onsite visit at the office to work on a small project, discuss ideas, and meet the team.