Lead ML Engineer - Real-Time Matchmaking & Ranking

The Briefed; San Mateo (CA); On-site; USD 295,000 - 345,000; Full time

Benefits offered by this job

Healthcare & Wellness

401(k) Retirement Savings

HQ Campus Perks

Job summary

Roblox is seeking a Principal ML Engineer on Matchmaking to own the technical vision for ML models, objective functions, and ranking systems that govern server placements for players’ experiences. You will lead predictive modeling, real-time retrieval, and offline/online evaluation to balance latency, player utility, and compute costs.

The role emphasizes cross-functional leadership, mentoring engineers, and translating cutting-edge ML research into production gains across Discovery, Search, and

Qualifications

• 8+ years of professional experience delivering and scaling production ML systems for ranking, recommendation, personalization, or resource allocation.
• Deep expertise defining multi-objective loss functions, building predictive models, and deploying optimization algorithms under latency/resource constraints.
• Hands-on experience building end-to-end MLOps workflows (feature stores, real-time inference, training pipelines, evaluation).
• Mastery across multiple languages (Python, C++, Go, Java, or Luau) for data pipelines and infrastructure code.
• Ability to steer long-term product goals into iterative engineering milestones across teams.
• Bachelor’s degree in Computer Science, Software Engineering, ML, or related field (Master’s/PhD preferred).

Responsibilities

• Own the technical vision and ML strategy for matchmaking, connecting Discovery and Search to intelligent server placements.
• Formulate multi-objective utility functions balancing player compatibility, latency, join times, session length, retention, and compute costs.
• Build and deploy models predicting high-value player actions and long-term engagement using historical data and live state.
• Design candidate retrieval, ranking, and server-assignment algorithms with real-time latency constraints.
• Evolve ML infra, feature stores, training/serving pipelines, and online inference to minimize training-serving skew.
• Lead offline benchmarking and online A/B experiments to measure impact on retention and platform efficiency.
• Mentor senior engineers and align architecture with Search, Discovery, Data/AI Infra, and Product teams.

Skills

ML engineering

Optimization

Distributed systems

Programming languages

Cross-functional leadership

Education background

Education

Bachelor's degree in CS/SE/ML

Job description

Roblox is seeking a Principal ML Engineer on Matchmaking to own the technical vision for ML models, objective functions, and ranking systems that govern server placements for players’ experiences. You will lead predictive modeling, real-time retrieval, and offline/online evaluation to balance latency, player utility, and compute costs.

The role emphasizes cross-functional leadership, mentoring engineers, and translating cutting-edge ML research into production gains across Discovery, Search, and