Research Engineer, SysML - FAIR

Meta's Fundamental AI Research (FAIR) team is seeking a Research Engineer specializing in SysML to push the boundaries of artificial intelligence. This role combines cutting-edge research with practical implementation at unprecedented scale. The position focuses on advancing AI through open science innovations, particularly in systems and infrastructure development.

The role involves working on fundamental challenges in AI systems, including distributed training optimization, development of training libraries, and hardware-software co-design. You'll be contributing to projects involving cuBLAS, cuDNN, FlashAttention, and other critical AI infrastructure components.

As a Research Engineer, you'll be responsible for conducting innovative research in machine learning systems, developing scalable solutions, and implementing efficient AI architectures. The role requires expertise in both theoretical machine learning and practical systems engineering, with a focus on sustainability and efficiency.

The ideal candidate should have at least a Master's degree in Computer Science or related field with 4+ years of relevant experience. Strong programming skills in languages like Python, C++, and Rust are essential, along with deep knowledge of machine learning frameworks, particularly PyTorch. Experience with large-scale ML systems and optimization is crucial.

At Meta, you'll be part of a team that's shaping the future of AI technology, with opportunities to publish research and directly impact product development. The position offers competitive compensation including base salary, bonuses, equity, and comprehensive benefits. You'll work alongside world-class researchers and engineers in an environment that values innovation and technical excellence.

This role is perfect for someone who is passionate about both research and practical implementation, with a strong desire to solve complex problems at scale. You'll have the opportunity to contribute to groundbreaking developments in AI while working on systems that affect billions of users worldwide.