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Senior Machine Learning Engineer, Dynamic Economics at Roblox
RobloxSan Mateo, CA, United States·8h ago
SeniorFull-timeRailsAWSMachine LearningData ScienceGitML
Salary Range
$132,600 - $179,400 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Senior Machine Learning Engineer to join the Economy ML team at Roblox. This role focuses on building models that power ranking, personalization, pricing, and optimization across Roblox’s economic surfaces, including Marketplace, Developer Monetization, and Payments.
Key Responsibilities
- →Design and implement end-to-end ML solutions for ranking, recommendation, pricing, and content understanding across Economy surfaces.
- →Build and iterate on deep learning retrieval and ranking models that personalize item and widget ordering across the Marketplace.
- →Develop models and policies that optimize pricing, conversion, and revenue while balancing ecosystem health.
- →Own the full ML lifecycle for projects, including data exploration, feature engineering, model design, training, evaluation, and production deployment.
- →Design and run robust experiments, tying work to core metrics such as engagement, bookings, and creator earnings.
- →Partner cross-functionally with Product, Backend, Data Science, Design, and other teams to define roadmaps and success metrics.
- →Ensure systems are scalable, reliable, observable, and extensible.
- →Contribute to the technical direction of the Economy ML team.
- →Mentor other engineers on ML best practices and experimentation.
Requirements
- ✓BS, MS, or Ph.D. in Computer Science, Machine Learning, Statistics, or a related technical field, or equivalent practical experience.
- ✓3+ years of experience with search, recommendation, personalization, pricing, or content understanding systems for a high-scale product.
- ✓Fluent in the ML lifecycle, including building and maintaining data pipelines and feature stores.
- ✓Deeply product-oriented, with a focus on impact on users, creators, and the business.
- ✓Technically strong in modern ML, with hands-on experience in deep learning for ranking/retrieval, representation learning, and large-scale training/inference.
