Engineering Manager, ML Infrastructure – Scale Production ML

Roblox Corporation; San Mateo (CA); On-site; USD 295,250 - 345,040; Full time

Job summary

Roblox Corporation is seeking an Engineering Manager for Machine Learning Infrastructure within Ads to lead a team of ML infrastructure engineers. You will shape scalable, production-ready ML systems for ads, drive architecture decisions, and partner with data scientists, engineers, and product teams to accelerate model development and deployment.

The role emphasizes strategic planning, mentorship, and building cost-efficient, high-performance infrastructure handling hundreds of billions of

Qualifications

• 5+ years of experience designing, building, and deploying large-scale ML systems in production.
• 2+ years of experience managing ML infrastructure engineers.
• End-to-End execution: built ML systems from data ingestion to serving in production.
• Team-first mindset with mentoring and enabling others to succeed.

Responsibilities

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

Skills

Machine learning systems

Team leadership

Roadmap planning

Mentoring

Education

BS/MS/PhD in CS/Engineering

Tools

ML platforms

Data pipelines

Model serving

Job description

Roblox Corporation is seeking an Engineering Manager for Machine Learning Infrastructure within Ads to lead a team of ML infrastructure engineers. You will shape scalable, production-ready ML systems for ads, drive architecture decisions, and partner with data scientists, engineers, and product teams to accelerate model development and deployment.

The role emphasizes strategic planning, mentorship, and building cost-efficient, high-performance infrastructure handling hundreds of billions of