What you will be doing:
You'll be working in a distributed team that explores innovative ways to make GPU and DPU accelerated applications easier to develop, deploy, and monitor.
Work on enabling GPUs and DPUs as first-class resources in Kubernetes container orchestrator.
This is an excellent opportunity to join the core group working on Cloud Native technologies enabling NVIDIA accelerators in the Kubernetes environment.
Work with engineering teams across NVIDIA to ensure your software integrates seamlessly with NVIDIA Cloud eco-system.
Automating and optimizing build, test, integration, and release processes for cloud native.
Efficiently multitasking with varied responsibilities to efficiently address evolving priorities.
What we need to see:
Bachelor’s or Master’s Degree in Computer Science or equivalent program from an accredited university/college, and 5+ years of hands-on software engineering.
Expert-level knowledge in a systems programming language (Go, C) and a solid understanding of data structures and algorithms.
Expertise in a scripting language (Bash, Python)
Strong understanding of Container Orchestration Systems (Kubernetes) and Container Technologies.
Experience working with GitLab or a similar SCM
Hands-on Automation experience in continuous integration frameworks like GitLab & ArgoCD.
Knowledge and experience working with system internals of Unix/Unix-like kernels such as Linux.
Strong background in cloud computing and distributed software design, and development.
Understanding of performance, security, and reliability in complex distributed systems.
Ways to stand out from the crowd:
Background with pub-sub models and message queues
Experience with developing Kubernetes Custom Resources and Operators, and deploying them in a cloud service provider
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