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Senior Machine Learning - Core AI
Senior Machine Learning - Core AIRoblox • San Mateo, California, United States
Senior Machine Learning - Core AI

Senior Machine Learning - Core AI

Roblox • San Mateo, California, United States
[job_card.30_days_ago]
[job_preview.job_type]
  • [job_card.full_time]
[job_card.job_description]

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 C++ and 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.
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