Key Responsibilities

• Building the compute platform and machine learning libraries for large scale machine learning and simulation workloads
• Focus on compute platform stability and efficiency on both CPU and GPU clusters, making the platform observable and scalable
• Utilize cluster monitoring and profiling tools to identify bottlenecks and optimize both infrastructure and software system
• Troubleshoot and resolve issues related to OS, storage, network, and GPUs

Challenges You Will Tackle: design, build and improve our compute platform for PB scale data model training and simulations with a wide range of machine learning models by leveraging our existing research infrastructure.

Requirements:

• Solid experience in running production machine learning infrastructure at a large scale
• Experience in designing, deploying, profiling and troubleshooting in Linux-based computing environments
• Proficiency in containerization, parallel computing and distributed training algorithms
• Experience with storage solutions for large scale, cluster-based data intensive workloads

Bonus qualification:

• Experience of supporting machine learning researchers or data scientists for production workloads

WHAT YOU CAN EXPECT FROM US:

In return for you joining our elite team, you will be offered a competitive salary package as well as access to a plethora of Optiver-perks. To hear more about what it is like to work here and our great culture, apply now and take the first step towards the best career move you will ever make!

DIVERSITY AND INCLUSION

Optiver is committed to diversity and inclusion, and it is hardwired through every stage of our hiring process. We encourage applications from candidates from any and all backgrounds, and we welcome requests for reasonable adjustments during the process to ensure that you can best demonstrate your abilities.

PRIVACY DISCLAIMER

Optiver 重视个人信息的保护。请您在提供个人信息给我们之前，认真阅读Optiver China Privacy Notice, 了解我们如何收集及处理您的个人信息。

Personal information protection is of utmost importance to Optiver. Before you provide any personal information to us, we strongly urge you to read our Privacy Policy to acknowledge how we collect and process your personal information.