Nvidia Senior AI ML Storage Infra Software Engineer GPU Clusters 

United States, Texas 

851801594

What you will be doing:

• Collaborate closely with our AI and ML research teams to understand their storage infrastructure and tooling needs and obstacles, translating those observations into actionable improvements.

• Monitor and optimize the performance of our infrastructure ensuring high availability, scalability, and efficient resource utilization.

• Help define and improve important measures of AI researcher efficiency focused on storage aspect, ensuring that our actions are in line with measurable results.

• Collaborate with teams with varied strengths, including researchers, data engineers, and DevOps professionals, to build a seamless and coordinated AI/ML infrastructure ecosystem.

• Stay on top of the latest advancements in AI/ML technologies, frameworks, and effective strategies, and promote their implementation within the company.

What we need to see:

• BS or equivalent experience in Computer Science or related field, with 6+ years of shown experience in AI/ML and HPC workloads and infrastructure.

• Hands-on experience in using or operating High Performance Computing (HPC) grade infrastructure as well as in-depth knowledge of accelerated computing (e.g., GPU, custom silicon), storage (e.g., Lustre, GPFS, BeeGFS), scheduling & orchestration (e.g., Slurm, Kubernetes, LSF), high-speed networking (e.g., Infiniband, RoCE, Amazon EFA), and containers technologies (Docker, Enroot).

• Expertise in running and optimizing large-scale distributed training workloads using PyTorch (DDP, FSDP), NeMo, or JAX. Also, possess a deep understanding of AI/ML workflows, encompassing data processing, model training, and inference pipelines.

• Proficiency in programming & scripting languages such as Python, Go, Bash, as well as familiarity with cloud computing platforms (e.g., AWS, GCP, Azure, OCI) in addition to experience with parallel computing frameworks and paradigms.

• Passion for continual learning and keeping abreast of new technologies and effective approaches in the AI/ML infrastructure field.

• Excellent communication and collaboration skills, with the ability to work effectively with teams and individuals of different backgrounds.