Principal Machine Learning Engineer - Matchmaking

Roblox • San Mateo, CA

1d • $295,250 - $345,040 • Onsite

About The Position

As a Principal Machine Learning Engineer on the Matchmaking team, you will own the technical vision and execution for the models, objective functions, and algorithms that assign players to game servers. Matchmaking affects who plays together, network latency, and session quality, and supports satisfying play, repeat visits, long-term engagement, developer success, and Roblox growth. The role serves millions of players across hundreds of thousands of servers in global datacenters.

You will lead as an individual contributor, setting technical direction and mentoring engineers. You will build and evolve the data, feature, training, serving, and evaluation systems for matchmaking machine learning; partner with product and infrastructure teams; and use offline evaluation and online experiments to improve models and objectives. The position is based in an office in San Mateo, California, and office roles are onsite Tuesday through Thursday, with optional presence Monday and Friday unless otherwise noted.

Requirements

• At least 8 years of experience delivering and improving large-scale machine-learning systems for ranking, recommendation, personalization, or resource allocation.
• Experience defining objective functions, building predictive models, and deploying optimization algorithms that balance user and business outcomes with production latency, reliability, and resource constraints.
• Ability to break down long-term product requirements into iterative deliverable stages.
• Experience initiating and facilitating challenging technical decisions across multiple teams and organizations, with empathy and the ability to find common understanding.
• Deep technical expertise and a user-centered approach, considering the needs of Roblox users and internal engineers.
• Generalist approach, mastery of several languages and technologies, and ability to adapt to different situations.
• Willingness and ability to tackle data or machine-learning problems hands-on.
• Creative and strategic approach to difficult problems, including simplifying complexity and bringing in ideas from new places.
• BS in Computer Science or a related discipline.

Nice To Haves

• MS or PhD.

Responsibilities

• Own the technical direction and machine-learning strategy for matchmaking, connecting Discovery and Search to server placements that improve player experience, developer success, and Roblox growth.
• Define and evolve the matchmaking objective function, balancing player and developer utility with system efficiency and making tradeoffs among co-player compatibility, network and join latency, engagement, retention, server utilization, and compute cost explicit and measurable.
• Build models that predict high-value actions and longer-term outcomes for player–server matches, including co-play, chat engagement, sustained play, and return visits, using player history, game characteristics, and live server state.
• Design and productionize candidate-server retrieval, ranking, and assignment algorithms that optimize the objective under real-time latency, capacity, and reliability constraints, accounting for joining players and players already in a server.
• Lead by example and through technical direction as an individual contributor, mentor engineers, and foster an engineering culture of excellence.
• Build and evolve data, feature, training, serving, and evaluation systems for matchmaking ML, ensuring fresh signals, reliable predictions, and consistency between training and serving.
• Partner with Discovery, Search, developer-facing product teams, modelers, and data and AI infrastructure engineers to co-design models and systems that adapt to each game’s needs and deliver value across the player journey.
• Define offline evaluation and lead online experiments to measure matchmaking’s impact on player engagement and retention, developer success, and system efficiency, using results to improve models and objectives.
• Translate research into iterative production improvements, collaborate with the wider ML community where applicable, and represent Roblox’s technical work.

Benefits

• Equity compensation for full-time employees.
• Benefits are referenced as described on the company benefits page, but specific benefits are not listed in the posting.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal