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A leading social technology company in Singapore is seeking a skilled engineer to optimize ML Infra performance for large-scale AI training and inference. In this role, you will identify performance bottlenecks and lead efficiency improvements in model training, collaborating with various teams. The ideal candidate has over 6 years of programming experience and a strong background in building large-scale infrastructure applications. This position offers opportunities to shape technical direction and drive cross-functional efforts.
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.