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Nvidia AI ML Infra Software Engineer GPU Clusters 
United States, Texas 
957502668

14.04.2025
US, CA, Santa Clara
US, WA, Redmond
time type
Full time
posted on
Posted 6 Days Ago
job requisition id

What you will be doing:

  • Collaborate closely with our AI and ML research teams to understand their infrastructure 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, ensuring that our actions are in line with measurable results.

  • Collaborate with diverse teams, 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 5+ years of proven 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) 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.

You will also be eligible for equity and .