AI/HPC Systems Performance Engineer

Summary

Meta's AI Training and Inference Infrastructure is growing exponentially to support ever increasing use cases of AI. This results in a dramatic scaling challenge that our engineers have to deal with on a daily basis. We need to build and evolve our network infrastructure that connects myriads of training accelerators like GPUs together. In addition, we need to ensure that the network is running smoothly and meets stringent performance and availability requirements of RDMA workloads. These workloads expect a loss-less fabric interconnect with minimal latency. To improve performance of these systems we constantly look for opportunities across stack: network fabric and host networking, comms lib and scheduling infrastructure.

Required Skills

AI/HPC Systems Performance Engineer Responsibilities:

• Lead multi-disciplinary teams to develop solutions for large scale training systems. Assess trade-offs of various solutions and make pragmatic decisions.
• Ensure timely milestone delivery with teamwork and close collaboration
• Responsible for the overall performance of the communication system, including performance benchmarking, monitoring and troubleshooting production issues.
• Defining technical vision and driving a multi-year roadmap to make progress towards the related objectives.
• Work with cross functional teams and provide guidance on the AI network architecture including topologies, transport, congestion control techniques.

Minimum Qualification

Minimum Qualifications:

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• Experience with developing, evaluating and debugging host networking protocols such as RDMA.
• 10+ years of experience in designing, deploying and operating networks.
• Experience with triaging performance issues in complex scale-out distributed applications.

Preferred Qualification

Preferred Qualifications:

• Experience with developing communication libraries, such as MPI, NCCL, and UCX.
• Understanding of AI training workloads and demands they exert on networks.
• Understanding of RDMA congestion control mechanisms on IB and RoCE Networks.
• Understanding of the latest artificial intelligence (AI) technologies.
• Experience with machine learning frameworks such as PyTorch and TensorFlow
• Experience in developing systems software in languages like C++

EOE

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [email protected].