2 months ago
San Mateo, CA, USASenior
Base Salary
$270k - $338k/yr
Responsibilities
- Design and implement scalable machine learning systems and production services.
- Develop, evaluate, and optimize models against real business problems.
- Build and maintain pipelines for data processing, feature engineering, training, validation, and deployment.
- Establish monitoring, observability, and model-performance tracking.
- Partner with product, data science, and software engineering teams to define and ship ML solutions.
- Drive architecture decisions for ML infrastructure and platform capabilities while reducing deployment cycle time.
- Mentor engineers, establish best practices, and ensure systems meet security, reliability, and compliance standards.
Requirements
- Typically 8+ years of experience in software or machine learning engineering.
- Strong experience deploying and operating machine learning systems in production.
- Strong Python and software engineering skills.
- Experience designing scalable distributed systems and data-intensive applications.
- Ability to own ML outcomes from design through production operation and make decisions based on experimentation and measurable results.
Benefits
- Highly competitive equity package for a foundational hire.
- Hybrid work model requiring approximately three days per week in the office in the Bay Area or NYC.
- Medical, dental, vision, and company-paid life insurance.
- Company contributions to Health Savings Accounts.
- 401(k) 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.
Tech Stack
Categories
About MrBeast
MrBeast (Beast Industries) is a media and entertainment company built around creator Jimmy Donaldson, producing large-scale YouTube videos and related digital content. The business spans advertising and sponsorships, and consumer products such as Feastables, supported by in-house studios with petabyte-scale production infrastructure. Founded in 2012 and headquartered in Greenville, North Carolina, it is privately held and known for philanthropic projects that reach a global audience.