About Polymarket

Polymarket is the world's largest prediction market platform. We enable individuals to express views on real-world events by trading on outcomes across politics, economics, sports, culture, and current affairs. Built as a peer-to-peer marketplace with no centralized "house," Polymarket aggregates diverse opinions into transparent, market-based probabilities that reflect collective expectations about the future.

We're growing fast, both in terms of volume ($21B traded in 2025) and adoption as an alternative news source. Our ambition is to become a ubiquitous beacon of truth in global media and we need your help adding fuel to the fire.

About the Role

The Growth Engineering team owns the systems that determine how people find Polymarket, what they do when they get here, and whether they come back. That means analytics infrastructure, martech integrations, experimentation frameworks, and the full-stack features that move conversion and activation numbers. It's a small, high-output team where the work is technical and the stakes are real.

We're hiring a Sr. Staff Engineer to be the technical foundation of that team. You'll own architecture decisions that affect how the entire team measures and ships work. You'll build and maintain the data pipelines that growth depends on, set the standard for how experiments are designed and evaluated, and ship full-stack features end-to-end without waiting on anyone else. This is not a coordination role. You will be writing code daily.

This hire matters because growth at Polymarket is accelerating and the infrastructure underneath it needs to scale with it. The person in this role will have direct influence on what gets built, how it gets built, and what gets retired. You'll do that as a senior IC with the trust and autonomy to make high-stakes calls, not someone who needs sign-off at every step.

What You'll Do

• Build and maintain Go-based data pipelines that power growth analytics, from event ingestion to reliable reporting that the team actually trusts.
• Audit existing martech integrations, identify what's underperforming or redundant, and replace or retire tooling with clear-eyed judgment.
• Architect and ship experimentation infrastructure that lets the team run clean A/B tests, measure results accurately, and move fast without breaking measurement.
• Ship full-stack growth features in Go and TypeScript, owning the work from backend service to frontend implementation without handing off.
• Bring ML where it adds real value, including personalization, predictive modeling, and experiment analysis, and build those systems into production, not just prototypes.