Principal Machine Learning Infrastructure Engineer (Ads & Discovery)

Location: San Mateo, California, United States. Office-based roles are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday.

Salary: $295,250–$345,040 USD base pay annually, plus equity compensation and benefits.

Company

Roblox builds tools and platforms for user-created 3D digital experiences and connects a global community of players, creators, and developers.

What you will do

• Build scalable, reliable, and high-performance machine learning infrastructure for Ads & Discovery.
• Co-design models and systems for recommendation, search, agentic applications, transformer architectures, LLMs, generative rankers, and content understanding.
• Design end-to-end systems spanning data pipelines, distributed training, low-latency inference, and production serving.
• Optimize KV-cache strategies, pruning, quantization, GPU utilization, memory efficiency, and custom kernels.
• Lead strategic planning and roadmap execution for production-ready training, feature engineering, serving, and inference systems.
• Partner with data scientists, ML engineers, platform teams, and product stakeholders to operate robust ML platforms.

Requirements

• 5+ years of experience designing, building, and deploying large-scale machine learning systems in production.
• 3+ years of experience technically leading ML infrastructure engineers.
• Experience with technologies such as FSDP, vLLM, SGLang, CUDA, distributed training frameworks, inference engines, and GPU kernels.
• Strong communication skills and a collaborative approach to problem solving.
• BS, MS, or Ph.D. in Computer Science, Engineering, or equivalent experience.
• For US-based roles, candidates must have US work authorization; future H-1B sponsorship may not be supported.

Culture & Benefits

• Work on large-scale systems serving hundreds of millions of users.
• Full-time employees are eligible for equity compensation and benefits.
• Commitment to equal employment opportunity and reasonable accommodations during the recruiting process.