Founding Engineer - Polynomic

The current ad market sucks. At Polynomic, we’re reimagining performance marketing from the ground up. We believe that ads, in various new forms, will continue to be the primary business model of the internet and the backbone of growth in commerce. Yet performance marketing today is heavily dependent on outdated playbooks, guesswork, manual effort. We believe that brands shouldn’t have to throw spaghetti at the wall and hope to get lucky to find growth. We are at an inflection point with AI and have a unique opportunity to make ads more efficient and profitable for brands through our agentic platform.

We are building autonomous, intelligent systems where brands can plug in and find the most profitable ways to grow their revenue through ads, instead of having to hire expensive agencies or spend countless hours optimizing ad campaigns.

Polynomic was founded by (ex Google Ads, Citadel, HBS, Harvard) and (ex Google Research, HBS, Stanford CS). Madhav launched a new AI ads product (0 -> $675M ARR) at Google, and Nathan launched Google’s first transformer model in production. Our team comes from Palantir, Google, Jane Street, Citadel, and Two Sigma. We’re a well-funded seed stage startup backed by top VCs and angel investors and already have multiple high-growth consumer brands as paying customers.

Role:

As a Founding Engineer, you’ll define and build the core technology stack that powers Polynomic. You’ll work on frontier AI problems, data infrastructure, and agent orchestration to build autonomous, intelligent systems to deliver the next generation of performance marketing.

Preferred Experience:

• Exceptional talent shows up in a lot of forms. You've demonstrated unusually strong ability and pace through shipped products, research, open-source, startups, competitions, or other deeply technical work

• You’re excited to own and deliver on ambitious, ambiguous projects that involve solving hard technical challenges (SFT/RL, bandits, reasoning, multi-agent systems, alpha research, world state modeling, large datasets with confounding and hidden variables, open-ended action spaces)

• You care about the problem of running efficient digital ads and recognize their impact on global commerce

This is an in-person opportunity in New York.

Compensation:

• $180k-$275k + 0.5-1.5% equity

• 401k, fully funded medical, dental, and vision insurance

• Relocation support to move to NYC