Overview

Meta is seeking a Software Engineer to join our AI Applications Engineering team. The ideal candidate has experience maximizing the performance of AI models on GPUs or custom silicon and will apply these skills to GenAI and Recommendation workloads on Meta's Training and Inference Accelerator (MTIA). This team focuses on maximizing training and inference performance and works cross-functionally with partner teams to deliver end-to-end performance for large-scale pre-training and inference that powers next-generation AI experiences.

Responsibilities

• Work cross-functionally to co-design models to maximize pre-training and inference efficiency
• Apply and drive state-of-the-art optimization techniques to large-scale AI workloads running on Meta’s accelerators, including functional development and maintenance
• Profile, analyze, debug, and optimize large-scale workloads on MTIA-scale training and inference systems
• Optimize the underlying processes of the vertical stack, from kernels, frameworks, communication, and firmware to model layers and hyperparameters
• Lead large and complex technical efforts across many engineers and teams from concept to implementation

Minimum Qualifications

• Bachelor’s degree in computer science or a related STEM field
• Experience programming AI accelerators (e.g., GPUs, custom silicon) using AI frameworks such as PyTorch or similar
• Experience developing custom kernels and compiler infrastructure to improve performance using low-level programming models such as CUDA, OpenCL or similar
• Minimum 5+ years of experience developing and optimizing performance in modern C/C++
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment

Preferred Qualifications

• Experience with training and validating large-scale AI models, including parallelising models across several accelerators
• Understanding of multiprocessing, including race conditions and inter-process communication
• Experience evaluating model performance, e.g., with profilers and tuning hyperparameters
• Thorough understanding of model and data parallelisms such as FSDP, tensor parallelism, model parallelism, expert parallelism, etc.
• Demonstrated experience with the model life cycle from pre-training and post-training to inference, datasets and metrics, especially for large language models
• Experience developing, optimizing and validating kernels on GPUs or other accelerators

About Meta

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.

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

Employment information

• Seniority level: Not Applicable
• Employment type: Full-time
• Job function: Engineering and Information Technology
• Industry: Technology, Information and Internet

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Location: London, England, United Kingdom