Engineering Manager (ML Infrastructure)

TL;DR

Engineering Manager (ML Infrastructure): Building and optimizing large-scale ads machine learning infrastructure to deliver performance ads to hundreds of millions of users with an accent on scalability, reliability, and cost-effectiveness. Focus on leading strategic planning for model training, data pipelines, and model inference systems.

Location: Hybrid in San Mateo, CA (Onsite Tuesday, Wednesday, and Thursday)

Company

A global platform empowering a community of developers to create immersive 3D experiences.

What you will do

• Lead strategic planning and roadmap execution for production-ready ML systems, including model training, data pipelines, and model inference.
• Own the architecture and establish engineering best practices for scalability, reliability, and cost-effectiveness of ML infrastructure.
• Collaborate with data scientists, ML engineers, and product stakeholders to design and operate robust ML platforms.
• Recruit, mentor, and grow a high-performing team of ML infrastructure engineers.

Requirements

• 5+ years of experience designing, building, and deploying large-scale ML systems in production environments.
• 2+ years of experience managing ML infrastructure engineers.
• Proven track record of end-to-end execution from data ingestion to serving in production.
• BS, MS, or Ph.D. in Computer Science, Engineering, or equivalent experience.
• Must have valid United States work authorization (some visa categories and H-1B sponsorship may not be supported).

Culture & Benefits

• Hybrid work model with required office presence three days a week.
• Eligibility for equity compensation and comprehensive benefits package.
• Opportunity to work on high-scale systems handling hundreds of billions of engagements.
• Commitment to equal employment opportunities and inclusive workplace culture.