Job description
Overview In this role you will build and operate the ML infrastructure that powers Roblox's virtual economy, including ranking, personalization, and pricing models. You'll work with cross-functional teams to deploy models at scale and improve throughput, latency, and reliability across Marketplace, Payments, and Developer Monetization. You'll shape the ML platform, mentor engineers, and drive impactful, data-driven decisions for creators and users. This is a chance to influence how millions interact with economy-driven experiences on Roblox.
Compensation / Benefitsequity compensation
competitive base salary ($243,290-$295,250)
onsite days (Tue-Thu) with possible Mon/Fri
equal employment opportunities
reasonable accommodations during recruiting
benefits as described on the page
ResponsibilitiesBuild and operate training infrastructure for ranking, recommendation, and pricing models
Co-design models and systems to optimize training and inference (GPU utilization, latency, mixed precision)
Design backend services and APIs to expose model predictions with latency budgets and fallbacks
Scale batch and real-time data pipelines and feature stores for training and serving
Own the path from trained models to production serving (packaging, deployment, versioning, canary/shadow rollouts, A/B experiments)
Improve reliability and observability through logging, monitoring, and on-call practices
Collaborate with central ML platform, data infrastructure, and other economy teams to adopt and contribute improvements
Contribute to technical direction of training/serving stack, balancing model quality, latency, and cost
Mentor engineers through design reviews, code reviews, and hands-on guidance
Key requirements5+ years software engineering experience
2+ years building and operating ML infrastructure or ML-backed production services at scale
Python and at least one other backend language
Hands-on experience training and serving deep learning models in production with PyTorch
GPU scaling and deployment on GPU inference servers
Experience building batch and streaming data pipelines and feature stores (e.g., Spark, Flink, Kafka)
Ability to debug and operate production health, monitoring, and incident response
Strong collaboration skills across ML engineers, platform teams, product managers, and data scientists
BS/MS/PhD in CS/Engineering or equivalent practical experience
cross-functional collaboration
ownership and accountability
strong communication
Python
PyTorch
distributed systems
Worksite address
San Mateo, CA, 94401, US
Who can apply
Review the original listing for location, eligibility and application requirements.