Machine Learning Engineer, Training Infrastructure

Overview

We are looking for an ML Engineer with 3+ YOE in high-performance computing systems to manage and optimize our computational infrastructure for training and deploying our machine learning models. The ideal candidate has diverse experience managing ML workloads at scale, supporting our 3DVAE and video diffusion models. We encourage you to apply even if you don’t meet every requirement — we value curiosity, creativity, and the drive to solve hard problems.

Responsibilities

• Design, implement, and maintain scalable computing solutions for training and deploying ML models, ensuring infrastructure can handle large video datasets.
• Manage and optimize the performance of our computing clusters or cloud instances, such as AWS or Google Cloud, to support distributed training.
• Ensure that our infrastructure can handle the resource-intensive tasks associated with training large generative models.
• Monitor system performance and implement improvements to maximize efficiency and utilization, using tools like Airflow for orchestration.
• Collaborate across research teams to understand their computational needs and provide appropriate solutions, facilitating seamless model deployment.

Qualifications

Benefits

Location : San Francisco, CA

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