Software Engineer, Model Lifecycle and Signals
Candidate
SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars.
SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next.
About the Role
As a Software Engineer on the Model Lifecycle and Signals team at SpaceXAI, you'll own the bridge between frontier models and every user facingCursor product, used at a scale few teams ever see. You'll decide when we 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.
Every improvement you make compounds across our products and every model we ship.
What you'll work on
- Get new frontier models into users' hands the day they're ready, and retire old ones without anyone noticing.
- Evaluate internal and external preview models before launch and give meaningful feedback to the teams building them.
- Build Cursor Router: decide which model handles each request, balancing quality, speed, and cost at massive scale.
- Build the eyes and ears of the product, and the experimentation platform that puts them to work: signals that show where each model shines, where it goes off track, and what 'better' actually means.
You may be a fit if
- You're an exceptional engineer with a track record of shipping production systems people rely on. You own problems end to end, and you'd rather automate a painful process than repeat it.
- You've built and operated evaluation, measurement, or model serving systems, such as AI evals, experimentation, ranking/relevance, or routers. You can turn ambiguous "quality" questions into concrete metrics, pipelines, and decisions.
- You're fluent with data and can collaborate effectively with data scientists and researchers.
- You have strong taste and real curiosity about model and agent behavior. You try new models the day they come out and have opinions about where each one shines.
#LI-DNI
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