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[2027] Senior Machine Learning Engineer - PhD Early Career

Roblox - San Mateo, CA, United States - Hybrid - posted 2026-10-08

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Salary: USD 196,750 - 243,290 / annual

Roblox is seeking a Senior Machine Learning Engineer to own high-impact ML projects end-to-end, from ideation through production deployment and academic publication. You will solve complex, high-dimensional challenges at world-scale concurrency, directly shaping the experience for millions of daily active users on the Roblox platform. In this role, you will prototype and implement advanced AI and machine learning solutions that drive core platform features and innovation. You'll develop and deploy cutting-edge models including deep learning, generative AI, and multimodal architectures to address complex technical challenges. Working closely with applied researchers, engineers, and product teams, you'll translate advanced research concepts into production-ready systems that scale to hundreds of millions of daily active users. Your expertise will span research areas such as Computer Vision and Graphics, multimodality, NLP, recommendation systems, or reinforcement learning. You'll work backward from user and product needs to architecture, delivering ML solutions that improve platform engagement, safety, and content ecosystem growth. The role emphasizes translating complex research into scalable, robust infrastructure with direct impact at global scale. Roblox operates on a hybrid schedule: onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday. REQUIREMENTS: - PhD in computer science, engineering, or related field, with thesis aligned to Roblox's research areas (or pursuing PhD) - Deep expertise and curiosity in a relevant technical domain: deep learning, computer vision, NLP, reinforcement learning, or distributed systems - Proficiency in one or more programming languages (Python, C++, Go, Java) and experience building and optimizing large-scale systems - Strong research track record evidenced by multiple publications and presentations in rigorous peer-reviewed venues

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