Senior Machine Learning Infrastructure Engineer, Ads

With Roblox Ads business growing at a rapid rate, we are building large scale ads machine learning infrastructure to deliver effective performance ads to our users, and more business values to our advertisers.

As a Senior Machine Learning Infrastructure Engineer in our Ads ML Infra team, you’ll build scalable, reliable, and high-performance infrastructure that powers ML systems across our organization. You’ll operate at the scales of hundreds of billions of engagements, and redefine how we deliver performance ads to hundreds of millions of users. 

You Will:

• Lead the technical strategy and implementation of scalable ML infrastructure including model training, data pipelines, feature engineering and model inference.


• Shape the team’s technical vision by helping define the roadmap, establishing foundational architecture, and driving key execution milestones.


• Mentor and support junior engineers, setting strong technical standards and fostering a culture of collaboration and learning.


• Work closely with data scientists, ML engineers, platform teams, and product stakeholders to design, implement, and operate robust ML platforms that accelerate model development and deployment.


• Own the architecture, scalability, reliability, and cost-effectiveness of ML infrastructure (e.g., training, serving, feature).


• Dig into performance bottlenecks all along the ML stack, spanning from model optimizations to infrastructure optimizations.


• Ensure high operational excellence in deployed ML infrastructure (monitoring, alerting, incident response).


• Stay abreast of industry trends in machine learning and infrastructure to ensure the adoption of leading-edge technologies and practices.

You Have:

• 5+ years of experience and a proven track record of designing, building, and deploying large-scale machine learning systems in production environments.


• Impact driven mindset: prioritizing product impact, reliability, and measurable success over code volume or complexity.


• Strong communication skills and a collaborative approach to problem solving.


• BS, MS, or Ph.D. in Computer Science, Engineering, or equivalent experience.