Senior ML/AI Engineer

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

About Us

Beast Industries is a multifaceted media and entertainment company founded by Jimmy Donaldson, popularly known as MrBeast, the most watched person in the world. Renowned for revolutionizing digital content creation, Beast Industries encompasses a diverse portfolio of ventures that extend far beyond its origins on YouTube. With a mission to entertain, inspire, and create significant social impact, Beast Industries operates across various domains including digital media, philanthropy, consumer products, and innovative business initiatives. At Beast Industries, we believe in the transformative power of digital media and its potential to entertain, educate, and effect positive change. Our commitment to innovation, creativity, and philanthropy drives us to explore new frontiers, create unforgettable experiences, and build a legacy that inspires future generations.

Location: Bay Area (San Francisco / Peninsula)  Reports to: Director of Engineering

The Opportunity

We are building a first-of-its-kind consumer membership ecosystem from the ground up — and AI is the substrate, not a feature bolted on at the end. As a Senior ML/AI Engineer, you will be one of the first engineers on the ground helping build the AI operational backbone and shipping the AI-native features that 100M+ users will actually touch. There is no legacy stack, no retrofitted pipelines, no model zoo to clean up — just a zero-to-one build where AI-native is the default assumption.

This is a hands-on IC role. You'll write the infra, ship the features, and build the evals that keep everything honest — working alongside product squads moving fast.

The Product

You will build AI inside a membership app anchored around the MrBeast audience — a product that will reach 100M+ users. 

What You'll Do

• Ship AI-native features end-to-end — recommendation, personalization, ranking, moderation, agents — working directly inside product squads.
• Help build and extend the AI operational backbone: model serving, inference infrastructure, retrieval, and prompt/agent tooling that other squads will rely on.
• Own evals for the features you ship — offline and online — so quality regressions get caught before users see them.
• Make pragmatic calls across foundation models, fine-tuning, RAG, and agent frameworks. Keep the stack lean and the feedback loops tight.
• Operate AI-native: burning through tokens, using coding agents daily, and shipping features faster than a traditional ML workflow would allow.

Who You Are

• Consumer-Scale Shipper: You've shipped ML or AI systems in production for products used by millions. You've been on-call for a model, not just trained one.
• AI-Native: You aren't just curious about AI; you are burning through tokens, using coding agents daily, and integrating modern AI tooling deeply into your workflow.
• Eval-Minded: You believe shipping AI without rigorous evals is shipping blind, and you've built or heavily contributed to eval systems that actually caught real regressions.
• Scrappy & Scaled: You have the startup experience to build from zero with a nimble team, plus the big-tech exposure to know what breaks when a product hits consumer scale.
• Action-Oriented: You thrive in ambiguity and prefer shipping over process. You'd rather spin up a prototype and show it than run a design review.