Senior Machine Learning - Avatar, Core AI

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As a Senior Machine Learning Engineer, you will work on challenging problems leveraging state-of-art AI/ML to empower a new generation of Roblox experiences for our growing community of users. We are looking for senior AI/ML engineers to lead the vision of low compute cost, in experience machine learning at Roblox, taking leads on designing core components of on-device ML operations. We are designing a system for advancing model architecture, enabling more efficient deployment to cloud and client, while delivering on complex operations including Generative AI model deployment. The engineer will be driving the architecture optimization across a large range of compute devices, making efficient use of available compute resources. Join us in our exciting journey! You will: Develop and implement state-of-the-art ML models Stay up-to-date with the latest research in ML and related fields, and apply this knowledge to improve the model performance Establish a pipeline for delivering Roblox ML model on range of computing devices Build cross-functional partnership on deployment and architecture optimization Design and implement primary components of the in-experience machine learning system. You have: 2+ years experience in developing machine learning models, preferably in image, video, audio or 3D representations with Python A strong understanding of deep learning frameworks including PyTorch and Tensorflow. Experience in shipping ML features in production environments, including low powered devices. Excellent cross-functional skills, partnering with organization leaders, driving to a conclusion. Knowledge in state-of-the-art deep learning network architectures and primitives. Experience with model optimization techniques. For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page . Annual Salary Range $195,780 — $242,100 USD Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted). Roblox provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Roblox also provides reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process. For US based roles only, please note 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.

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