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A leading company in technology is seeking an experienced professional to optimize machine learning infrastructure for large-scale AI systems. This role involves identifying efficiency opportunities, improving performance, mentoring teammates, and driving cross-functional collaborations. The ideal candidate has extensive experience in programming and large-scale infrastructure applications and holds a degree in a relevant technical field.
The MRS ML Infra team is focusing on ML Infra performance and efficiency for both large scale AI training and inference workflows in the recommendation domain.
In this role, you will work on optimizing the e2e stack for model training and inference for large scale recommendation models, with opportunities coming from the domains of distributed systems, model/system co-design, GPU optimizations, and more.
While the core of day-to-day work and key responsibility will be to identify and lead the execution for short/mid-term opportunities for efficiency optimization, you will also drive long term strategies and shape team direction on things like model/system co-design, performance automation, regression detection and mitigation, etc.
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.