Senior Machine Learning Engineer - PhD Early Career

Join Roblox to help shape advanced AI and machine learning systems that reach hundreds of millions of daily active users. In this Senior Machine Learning Engineer role for PhD early career, you will take AI/ML work from ideation to production deployment, with an emphasis on translating research into scalable infrastructure that supports platform engagement, safety, and content ecosystem growth.

What you’ll do

• Prototype and implement advanced AI and machine learning solutions that enable core platform features and drive innovation at scale.
• Develop and deploy cutting-edge models, including deep learning, generative AI, and multimodal architectures, to address complex, high-impact problems.
• Partner with applied researchers, engineers, and product teams to convert advanced research ideas into production-ready systems.
• Translate research into scalable, robust infrastructure that delivers measurable impact across a large user base.
• Start from user and product needs, then work backward to architect ML solutions that improve engagement, safety, and content ecosystem growth.

What you bring

• Possess or be pursuing a PhD in computer science, engineering, or a related field, with a thesis aligned to Roblox’s research areas.
• Deep expertise and curiosity in a relevant technical domain such as deep learning, computer vision, NLP, reinforcement learning, or distributed systems.
• Proficiency in one or more programming languages (for example, Python, C++, Go, or Java) and experience building and optimizing large-scale systems.
• A strong research track record with multiple publications and presentations in rigorous peer-reviewed venues.

Tools and technologies

Python, C++, Go, Java, deep learning, generative AI, multimodal architectures, computer vision, NLP, reinforcement learning, distributed systems.

Compensation and workplace details

Location: San Mateo, CA, United States (onsite).

Annual Salary Range: USD 196,750 - 243,290. The actual base pay depends on job-related factors including professional background, training, work experience, location, business needs, and market demand.

All full-time employees are eligible for equity compensation and benefits as described on this page.

Roles based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).

Additional notes

As you apply, you can find more information about the process by signing up for SPEAK_, where you will access a practice assessment, comprehensive guides, FAQs, and modules designed to help you complete the hiring process.

US-based roles only: The company may not be able to employ candidates for this role who have United States work authorization related to certain U.S. visa categories, or support future H-1B sponsorship at this time.