Systems Software Engineer, Kubernetes Scale

🕒 June 26

🌐 Germany, France, +1 more countries – Remote

🇩🇪 Germany – Remote 🇫🇷 France – Remote 🇵🇱 Poland – Remote

💵 zł176.3k - zł383.5k / year

⏰ Full Time

🟢 Junior

🟡 Mid-level

🔙 Backend Engineer

👻 Ghost score 38%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Drive end-to-end performance and scale characterization for the NVIDIA DGX Cloud software stack, from Kubernetes control and data planes through GPU Operator, Network Operator, DCGM, NIM, and distributed inference serving • Collaborate with AI researchers, developers, and customers to develop automated tests simulating real user workloads • Investigate performance and scale issues in complex distributed systems and identify root causes • Design and develop monitoring, reporting, and analysis tools for performance and scale testing across software, GPU, and CPU resources • Triage, debug, and resolve issues related to operating Kubernetes clusters at ultra-large scale • Build and maintain a continuous performance and scale testing framework through a modern CI/CD pipeline • Document research, methodologies, and results and present findings at internal and external venues, including KubeCon and GTC • Engage with Kubernetes, CNCF, and NVIDIA open-source communities to validate AI workload performance and influence design decisions

🎯 Requirements

• 2+ years of experience in Computer Architecture, Networking, Storage systems, Accelerators • Bachelor's/Master's in Engineering, preferably Electrical Engineering, Computer Engineering, or Computer Science, or equivalent experience • Expertise in Kubernetes and familiarity with related CNCF projects • Experience with large-scale parallel and distributed accelerator-based systems • Expertise optimizing performance and AI workloads on large-scale systems • Experience with performance modeling and benchmarking at scale • Proficiency in Golang/Python • Background with the NVIDIA software ecosystem in both training and inference domains • Expertise with at least one public CSP infrastructure (GCP, AWS, Azure, OCI, for example) • Strong operational experience with a Kubernetes distribution • Prior experience scaling Kubernetes clusters to ultra-large node and object counts • Demonstrated history of working in the open-source community • Excellent communication and interpersonal abilities • PhD in relevant areas is a standout qualification