Senior / Principal Infrastructure Engineer - ML Platform

Job Summary

At Roblox, we are building the tools and platform that empower our community to bring any experience they can imagine to life. We are looking for talented engineers to join our ML Platform team and help us design, scale, and maintain the foundational infrastructure powering our entire machine learning ecosystem.

About the Role

As an Infrastructure Engineer on the ML Platform team, you will design, scale, and maintain the foundational infrastructure powering our entire machine learning ecosystem. You will set technical strategy and oversee development of high-scale and reliable infrastructure systems. You will propose and implement new platform tooling to improve time to production for ML Engineers and Data Scientists across the full ML lifecycle. You will partner across organizations to build tooling, interfaces, and visualizations that make the ML@Roblox a delight to use.

Responsibilities

• Bootstrap and maintain Kubernetes and Cloud infrastructure for ML Platform components including Serving Layer, Metadata Store, Model Registry, and Pipeline Orchestrator.
• Set technical strategy and oversee development of high-scale and reliable infrastructure systems.
• Propose and implement new platform tooling to improve time to production for ML Engineers and Data Scientists across the full ML lifecycle.
• Work on infrastructure projects such as GPU fleet management, hybrid-cloud orchestration, and writing custom Kubernetes controllers and resources.
• Stay abreast of industry trends in machine learning and infrastructure to ensure the adoption of leading-edge technologies and practices.
• Partner across organizations to build tooling, interfaces, and visualizations that make the ML@Roblox a delight to use.

Requirements

• 6+ years of professional experience and a tool chest of system design experience upon which to draw to build scalable, reliable platforms.
• Deep experience with Kubernetes (K8s) and cluster management at scale — e.g., managing 100s–1000s of nodes, serving 100k+ QPS, and ideally having experience writing custom Kubernetes controllers.
• Strong proficiency in Infrastructure as Code (IaC), specifically using Terraform to bootstrap, manage, and automate cloud infrastructure across AWS, GCP, or similar environments.
• Experience with the end-to-end ML model lifecycle such as model serving, training, model CI/CD, and GPU resources management, and have built ML platform features that are delightful to use.
• Proficiency in DevOps tooling such as Docker, Kubernetes, CI/CD systems, and bootstrapping cloud infrastructure (AWS, GCP, etc.).
• Automation advocate: you're passionate about infrastructure-as-code and automating painful manual processes.
• Reliability nut: you love digging into tricky postmortems and identifying weaknesses in complicated systems.
• Passionate about supporting internal partners (data scientists and ML Engineers) to meet and understand their needs.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Data Science, or a similar technical field or equivalent practical experience.

Benefits

We offer a competitive compensation package, including a range of benefits such as health insurance, retirement plans, and paid time off. We also provide a collaborative and inclusive work environment where you can grow your skills and contribute to making a positive impact on the world.

Pay

The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range.

Annual Salary Range $278,530—$345,040 USD

Schedule

Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).