Requirements

B.S./M.S. degree in CS/CE or equivalent experience with 5+ years of relevant experience
Experience with parallel programming and at least one communication runtime (MPI, NCCL, UCX, NVSHMEM)
Excellent C/C++ programming skills, including debugging, profiling, code optimization, performance analysis, and test design
Experience working with engineering or academic research community supporting HPC or AI
Practical experience with high performance networking: Infiniband/RoCE/Ethernet networks, RDMA, topologies, congestion control
Expert in Linux fundamentals and a scripting language, preferably Python
Familiar with containers, cloud provisioning and scheduling tools (Docker, Docker Swarm, Kubernetes, SLURM, Ansible)
Adaptability and passion to learn new areas and tools
Flexibility to work and communicate effectively across different teams and timezones

Nice to Haves

Experience conducting performance benchmarking and developing infrastructure on HPC clusters
Prior system administration experience, especially for large clusters
Experience debugging network configuration issues in large scale deployments
Familiarity with CUDA programming and/or GPUs
Good understanding of Machine Learning concepts and experience with Deep Learning Frameworks such as PyTorch, TensorFlow
Deep understanding of technology and passion for the field

Engage with our partners and customers to root cause functional and performance issues reported with NCCL
Conduct performance characterization and analysis of NCCL and DL applications on GPU clusters
Develop tools and automation to isolate issues on new systems and platforms, including cloud platforms
Guide customers and support teams on HPC knowledge and standard methodologies
Document and conduct trainings/webinars for NCCL
Engage with internal teams in different time zones on networking, GPUs, storage, infrastructure, and support