AI Capacity Planning Engineer

Meta•Menlo Park, CA

About The Position

Meta is seeking a Performance and Capacity Engineer to join the Capacity team to focus on AI strategy and planning projects. This person would be required to work cross-functionally with a number of teams to ensure optimal operation and growth of our AI computing resources from both a cost and technology perspective. Tens of billions of user requests, hundreds of peta bytes of data, thousands of giga bps of network flow. Help build one of the largest AI training and inference services in the world!

Requirements

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
8+ years of experience in performance or software engineering and/or optimization pertinent data science, data engineering or equivalent practical experience
8+ years of experience in designing and implementing models and optimization algorithms
4+ years of experience in coding/scripting languages such as Python, R, Java, C, C++, PHP
Experience working with distributed systems at scale
Experience in infrastructure operations and technical infrastructure knowledge
Experience working with cross-functional teams
Experience optimizing complex systems, working with large datasets, and driving business impact

Nice To Haves

MS or PhD degree in Computer Science, Electrical Engineering, Operations Research or other technical field
Experience working with large scale AI/ML systems (GPU based)
Direct experience in capacity planning for a major private or public cloud
Practical experience and demonstrated success in performance or capacity engineering

Responsibilities

Own AI infrastructure capacity planning for Meta: including Servers, Data Centers, Network
Design, implement and launch software systems to improve AI capacity planning efficiency and quality, partnering with software engineers
Contribute to end to end AI capacity planning processes, methodologies, and data to deliver executable and optimized plans
Manage and resolve critical escalations and exceptions in all areas of AI capacity planning
Build mathematical models to perform simulation and optimization studies of AI demand and supply projections, scenario planning, and feasibility analysis while balancing various constraints
Work cross-functionally to define problem statements, collect data, build analytical models and make recommendations to drive change and optimization at the most strategic levels
Partner across Infra: such as platform teams, operations, networking planning, data center planning as well as Product and Finance teams to find the most optimal ways to scale our AI Infrastructure
Effectively navigate complex tradeoffs and relationships to balance solving for team, cross-functional partner / stakeholders, and Meta company priorities. Balance the need to “keep things running” with longer-term, high-impact projects