Research Engineer, SysML - FAIR

Meta's Fundamental AI Research (FAIR) team is seeking a Research Engineer to join their SysML division, focusing on advancing artificial intelligence through innovative systems research. This role combines cutting-edge research with practical engineering to push the boundaries of AI systems.

The position involves working on fundamental advances in machine learning systems, with a focus on distributed training at unprecedented scales. You'll be developing and optimizing components like cuBLAS, cuDNN, and FlashAttention, while also working on training performance acceleration through hardware-software co-design.

As a Research Engineer, you'll be responsible for conducting research that enables better understanding of various data modalities (images, video, text, audio) and developing more efficient AI systems. The role requires expertise in both theoretical machine learning and practical system implementation, with a focus on scalability and sustainability.

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

Meta offers a competitive compensation package ranging from $70,670 to $208,000 annually, plus bonus and equity opportunities. The position is based in Menlo Park, CA, at Meta's headquarters, where you'll work with world-class researchers and engineers in the FAIR team.

This role offers the unique opportunity to contribute to cutting-edge AI research while implementing solutions that can be deployed at Meta's massive scale. You'll be at the forefront of developing sustainable and efficient AI systems that could shape the future of machine learning technology.

The position combines research publication opportunities with practical implementation, making it ideal for those who want to bridge the gap between academic research and industry application. You'll work on problems that require both theoretical insight and engineering expertise, with the resources and scale that only Meta can provide.