Join the NVIDIA Deep Learning Frameworks Infrastructure team as a Senior Systems Engineer focusing on High-Performance AI & Networking Applications, committed to ground-breaking AI & Networking Solutions. This position offers a distinctive opportunity to engage in the latest technology advancements, collaborating closely with elite teams to elevate NVIDIA's impactful innovations.
What you will be doing:
Collaborate with networking teams to plan, implement, and evaluate performance benchmarks on NVLINK, NVSwitch, and InfiniBand powered infrastructures.
Assess findings and work closely with framework, hardware, and support teams to improve system performance across various deep learning workloads.
Act as a primary resource for fixing networking and hardware integration issues, focusing on scalable multi-node systems.
Maintain high communication standards across multiple engineering, support, and R&D teams, ensuring technical and performance goals are met.
Offer technical mentorship and documentation for internal teams and external partners on standard methodologies in HPC networking deployments.
Share insights on improving networking strategies for substantial AI and deep learning infrastructure.
What we need to see:
BS/MS or PhD in Computer Science, Engineering, or related field, or equivalent experience.
8+ years of proven experience in AI/HPC Infrastructure.
Familiarity with AI/HPC job schedulers and orchestrators like Slurm, K8s, or LSF. Practical exposure to AI/HPC workflows employing MPI and NCCL.
Familiarity with High-Speed Networking pertaining to HPC including InfiniBand, RDMA, RoCE, and Amazon EFA.
Essential to have an understanding of PyTorch, MegatronLM, and Deep Learning Inference frameworks such as vllm/sglang.
Proven experience with InfiniBand, NVLINK, and high-speed networking technologies in HPC or large-scale datacenter environments.
Investigating and evaluating performance in multi-node systems, especially in deep learning or scientific computing tasks.
Strong analytical, debugging, and technical communication skills.
Comfortable working in collaborative, multi-faceted teams.
Ways to stand out from the crowd:
Mastery in deep learning frameworks or distributed training systems.
Familiarity with datacenter automation, advanced network protocols, and supporting large HPC or AI clusters in production environments.
Understanding of fast, distributed storage systems like Lustre and GPFS for AI/HPC workload.
Experience with networking and communications libraries like NCCL, NIXL, NVSHMEM, UCX.
Experience developing or maintaining cluster management and monitoring tools Ex: ansible for infrastructure as a service, prometheus and grafana for monitoring.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Top Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
