Senior ML/AI Engineer

Senior ML/AI Engineer

Primary: Bay Area (San Francisco/Peninsula) | Secondary: NYC

The Opportunity

We're building a consumer app and Brand x Creator network from the ground up, and advertising is core to how the business works. As a Senior ML/AI Engineer on advertising measurement and quality, you'll be building the ML that informs creator matching, ads/creative quality, and performance measurement. You get to build the measurement and quality layer from zero, AI-native by default, against an audience of 100M+ real people.

This is a hands-on IC role. You'll build the models, ship the measurement, and own the evals and experiments that tell us the truth about what's working.

The Product

You'll build the ML behind sponsorships and advertising across our global creator platform and consumer applications focused on the Beast audience, a footprint that reaches 100M+ users. 

What You'll Do

• Build and ship ML for ad and content quality and relevance: ranking, matching, and the quality and brand-safety models that decide what's good enough to run.
• Own measurement end to end: attribution, incrementality, and the experimentation systems (A/B and geo tests, holdouts, causal methods) that prove whether advertising actually moved the needle.
• Build the data and eval foundations that keep measurement honest, so a number we report to a partner is a number we trust.
• Make pragmatic calls across classical ML, modern LLM tooling, and causal inference. Use the right tool, keep the stack lean, keep the feedback loops tight.
• Operate AI-native: burning through tokens, using coding agents daily, and shipping faster than a traditional ML workflow would allow.

Who You Are

• Consumer-Scale Shipper: You've shipped ML in production for products or advertising systems used by millions. You've been on-call for a model, not just trained one.
• Measurement-Minded: You know the difference between a correlation and a causal lift, and you've built measurement or experimentation systems that held up to scrutiny. Attribution, incrementality, and experiment design are second nature.
• AI-Native: You aren't just curious about AI. You're burning through tokens, using coding agents daily, and building modern AI tooling into how you work.
• Scrappy & Scaled: You've got the startup chops to build from zero with a small team, plus the big-tech exposure to know what breaks when something hits real scale.
• Action-Oriented: You'd rather ship a prototype and show it than sit through a design review. Ambiguity doesn't slow you down.

What Success Looks Like

In this role, success means building ML and AI systems that are not only technically strong, but also reliable, scalable, and valuable in production. Over time, you will help improve the speed, quality, and maturity of how we develop and operate intelligent systems, while enabling new product capabilities powered by machine learning and modern AI.

What Success Looks Like

You’ll have the opportunity to work on meaningful ML and AI problems, collaborate with strong cross-functional partners and help shape the next generation of intelligent products and workflows at scale. This is a great role for someone who wants to combine hands-on engineering with real-world AI impact.

The target total compensation ranges from $170,000 to 223,000, an employee equity plan grant, bonus, plus comprehensive benefits.