Research Engineer, Hardware (Phd)
Posted on 3/8/2022
Seattle, WA, USA • Washington, USA • Austin, TX, USA • Menlo Park, CA, USA
- Currently has, or is in the process of obtaining, a PhD in Computer Science, Electrical Engineering, Operations Research or related field
- Publications in conferences/journals or experience in artificial intelligence, machine learning, computer architecture, operating systems, data center technologies, performance analysis, workload characterization, or related field
- Experience in leveraging theoretical and empirical research to solve problems
- Experience in communicating complex research in a clear, precise, and actionable manner
- Coding and scripting proficiency
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
- Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
- Explore and develop novel solutions to scale one of the largest data center capacities in the world: work with Services, Product, Data, and Infrastructure teams to scale the data center infrastructure including tens of billions of user requests, hundreds of petabytes of data, and thousands of giga bps of network flow
- Perform research and make recommendations aimed at tackling state-of-the-art hardware and software performance issues (e.g. optimize hardware and software architectures, improve product/service performance, reduce resource consumption and shorten request latency, etc.)
- Provide deep visibility into Meta products and services: Run capacity and performance experiments to determine scaling and utilization parameters for various service tiers
- Collaborate with wider Infrastructure teams to land improvements to server and network hardware and optimizer software architecture
- Research experience in one or more of the following areas - Distributed storage systems, optimizing AI/ML systems and traditional (Caches, Databases) distributed applications
- Expertise with analysis and conducting performance characterization of distributed systems with focus on hardware and software co-design
- Understanding of hardware architecture of one or more key hardware components such as CPU, GPU, Memory, Flash, or related
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