Senior Machine Learning Engineer

Reposted Yesterday
San Mateo, CA, USA
In-Office
Senior level
News + Entertainment
The Role
Design, build, deploy, and operate production-grade ML systems and pipelines for a massive consumer audience. Own full lifecycle from data processing and feature engineering through training, validation, deployment, and monitoring. Drive ML infrastructure and architecture decisions, partner with product and data teams, optimize models against business metrics, and mentor engineers to ensure security, reliability, and compliance.
Summary Generated by Built In
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.

Senior Machine Learning Engineer

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


The Opportunity

We're doing an AI-first engineering rebuild for a company that already has an audience of 100M+ people. This is a zero-to-one build with no legacy constraints, so you get to stand up ML systems the right way from day one. You're here to ship machine learning that creates real, measurable value for a massive consumer audience.

The Product

You'll design, build, deploy, and operate ML systems that power the MrBeast ecosystem, bridging data science, software engineering, and platform engineering to ship production-grade capabilities. That means:

  • Build scalable ML systems and services that move real business metrics for an audience of 100M+ people.
  • Own the full lifecycle: pipelines for data processing, feature engineering, training, validation, deployment, and monitoring.
  • Set the bar for AI-first engineering, including how we test new model capabilities and bring them into production.

What You'll Do

  • Design and implement scalable ML systems and services for production.
  • Develop, evaluate, and optimize models against real business problems.
  • Build and maintain ML pipelines across data processing, features, training, validation, and deployment.
  • Establish monitoring, observability, and model-performance tracking.
  • Partner with product, data scientists, and software engineers to define and ship ML solutions.
  • Drive architecture decisions for ML infrastructure and platform capabilities, and cut deployment cycle time.
  • Mentor engineers, set best practices, and make sure systems meet security, reliability, and compliance bars.

Who You Are

  • AI-Native: You live and breathe this: you're already burning through tokens daily, and shipping ML is the job itself.
  • Production ML Builder: Typically 8+ years in software or ML engineering, with strong experience deploying and operating ML systems in production and solid Python and software engineering practice.
  • Systems Thinker: You've designed scalable distributed systems and data-intensive applications, and you know why a model that looks great offline can fail in production.
  • Evidence-Driven Owner: You decide with experimentation and measurable results, and you own outcomes from design through production operation.

Bonus points for MLOps platforms and automated model lifecycle management, cloud-native ML architectures and distributed training, responsible AI and model governance, and leading technical initiatives across multiple teams.

Benefits

  • Equity: Highly competitive equity package designed for a foundational hire.
  • Hybrid Model: Expected ~3 days per week in-office (Bay Area or NYC).

BenefitsThe Perks, Why Work On the MrBeast Team

We are redefining what entertainment and storytelling look like at global scale. Every piece of content we publish reaches millions and influences culture in real time. This is your opportunity to lead the team that decides how those moments come to life across every screen.

  • Competitive Salary
  • Generous Medical (Blue Cross Blue Shield), Dental, Vision and company-paid Life Insurance 
  • Company contributions to employee Health Savings Accounts (HSA) 
  • 401k Plan with Safe Harbor company-matching
  • Flexible vacation policy and paid company holidays
  • Company-provided technology package 
  • Relocation assistance where applicable, including travel and company-provided housing for the first 90 days

Skills Required

  • 8+ years in software or ML engineering
  • Strong experience deploying and operating ML systems in production
  • Solid Python and software engineering practice
  • Experience designing scalable distributed systems and data-intensive applications
  • Experience building ML pipelines: data processing, feature engineering, training, validation, deployment, and monitoring
  • Evidence-driven experimentation and measurable model evaluation
  • Mentoring engineers and setting engineering best practices
  • Experience with MLOps platforms, automated model lifecycle management, cloud-native ML, distributed training
  • Experience with responsible AI and model governance
Am I A Good Fit?
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The Company
HQ: Greenville, NC
113 Employees

What We Do

The YouTube Streamy Awards' 2020 Creator of the Year Accomplishments - Raised $20,000,000 To Plant 20,000,000 Trees - Given millions to charity - Donated over 100 cars lol - Gave away a private island - Given away over 100 ps4s lol - Gave away 1 million dollars in one video - Counted to 100k - Read the Dictionary - Watched Dance Till You're Dead For 10 Hours - Read Bee Movie Script - Read Longest English Word - Watched Paint Dry - Ubering Across America - Watched It's Every Day Bro For 10 Hours - Ran a marathon in the world's largest shoes - Adopted every dog in a shelter You get the point haha

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