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[2026] Senior Machine Learning Engineer, Engine Optimization - PhD Early Career

Roblox

$192,890 - $238,520
Dec 4, 2025
San Mateo, CA, US
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Roblox is looking to solve the problem of ensuring a stable, enjoyable, and interactive experience for its users across all devices by intelligently orchestrating and adjusting presentation quality from high-fidelity rendering down to basic interaction.

Requirements

  • Expertise in one or more areas of applied machine learning: reinforcement learning (RL) for control systems, resource scheduling, predictive modeling (especially time-series analysis for resource usage), or real-time optimization.
  • Proficiency in one or more programming languages (e.g., C++, Python, Go, Java) and experience designing, building, and deploying ML models in a performance-critical environment.
  • A strong understanding of low-latency, systems-level concepts (e.g., memory management, threading, operating system signals) is a significant advantage.
  • A track record of solving complex optimization problems or experience integrating AI/ML into core engineering products, preferably in gaming or mobile environments.

Responsibilities

  • Analyze massive-scale engine performance and user engagement telemetry to drive the team’s strategic roadmap, using data insights to prioritize high-impact optimization targets
  • Design and implement machine learning models to predict and manage critical engine resource constraints in real time.
  • Develop adaptive control systems that use ML outputs to dynamically adjust engine fidelity parameters, maximizing user experience while maintaining stability and low latency.
  • Collaborate with core engine and performance engineering teams to integrate ML solutions directly into the critical path of gameplay across multiple platforms.
  • Define the architectural roadmap for introducing and scaling ML infrastructure within the Harmony subsystem, ensuring reliable operation at massive scale.

Other

  • Bachelor's, Master's, or Ph.D. degree (redacted from resume if preferred)
  • Ability to work onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday
  • Equal employment opportunities and reasonable accommodations provided to candidates with qualifying disabilities or religious beliefs during the recruiting process
  • Must be eligible for equity compensation and benefits as described on the company website
  • Must be willing to sign up for Speak_ to access practice assessment, comprehensive guides, FAQs, and modules designed to help with the hiring process