Senior Systems Software Engineer – GPU Performance

NVIDIA

Senior Systems Software Engineer focusing on GPU Performance at Scale. Leading innovation in AI and GPU computing at NVIDIA with extensive experience required.

Posted 5/19/2026full-timeRemote • 🇵🇱 PolandSenior💰 PLN 292,500 - PLN 650,000 per yearWebsite

Tech Stack

Tools & technologies

CloudDockerLinuxPythonSwift

About the role

Key responsibilities & impact

Lead the implementation of performance practices in large-scale GPU infrastructure, delivering powerful tools, methodologies, and flows to validate and improve multiple datacenter products concurrently.
Align next-generation AI workloads with next-generation datacenter builds for NVIDIA GPUs, CPUs, and networking hardware.
Engage early with HW/FW/SW/platform internal and customer teams.
Develop engineering solutions that provide continuous insights into the performance of AI workloads in evolving environments, generating swift insights into improvements and regressions.
Decompose high-complexity performance or stability issues into minimal reproduction cases, working towards identifying the root cause.
Participate in collaborations with various SW and FW teams (BMC/SBIOS/OS/drivers, etc.) to develop outstanding methods and tools.
Analyze, debug, and resolve critical firmware and software issues to achieve the highest AI workload performance at scale.

Requirements

What you’ll need

Proven understanding of accelerated computing software stacks (CUDA).
Experience with modern cloud and container-based enterprise computing architectures, with Slurm preferred.
Strong programming and scripting experience in C/C++/Python/Bash.
Deep expertise in systems architecture and the impact of various components on performance.
Experience with container technology and Linux-based OSes, with Docker preferred.
Experience supporting high-performance computing or deep learning in engineering or academic research communities.
Strong teamwork and communication skills, coupled with results-focused analytical abilities.
BS in Engineering, Mathematics, Physics, or Computer Science (or equivalent experience); MS or PhD desirable with 10+ years of applicable experience.

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account NVIDIA Website LinkedIn All Job Openings 10,000+ employees Founded 1993 🤖 Artificial Intelligence 🎮 Gaming Artificial Intelligence
Gaming
Automotive 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. Senior Systems Software Engineer – GPU Performance 🔥 0 minutes ago 🇵🇱 Poland – Remote 💵 zł292.5k - zł650k / year ⏰ Full Time 🟠 Senior 🧑‍💻 Full-stack Engineer Cloud Docker Linux Python Swift Apply Now Find Hiring Managers Customize resume + cover letter Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 Description
Lead the implementation of performance practices in large-scale GPU infrastructure, delivering powerful tools, methodologies, and flows to validate and improve multiple datacenter products concurrently.
Align next-generation AI workloads with next-generation datacenter builds for NVIDIA GPUs, CPUs, and networking hardware.
Engage early with HW/FW/SW/platform internal and customer teams.
Develop engineering solutions that provide continuous insights into the performance of AI workloads in evolving environments, generating swift insights into improvements and regressions.
Decompose high-complexity performance or stability issues into minimal reproduction cases, working towards identifying the root cause.
Participate in collaborations with various SW and FW teams (BMC/SBIOS/OS/drivers, etc.) to develop outstanding methods and tools.
Analyze, debug, and resolve critical firmware and software issues to achieve the highest AI workload performance at scale. 🎯 Requirements
Proven understanding of accelerated computing software stacks (CUDA).
Experience with modern cloud and container-based enterprise computing architectures, with Slurm preferred.
Strong programming and scripting experience in C/C++/Python/Bash.
Deep expertise in systems architecture and the impact of various components on performance.
Experience with container technology and Linux-based OSes, with Docker preferred.
Experience supporting high-performance computing or deep learning in engineering or academic research communities.
Strong teamwork and communication skills, coupled with results-focused analytical abilities.
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Hard Skills & Tools

CUDACC++PythonBashsystems architectureperformance analysisdebugginghigh-performance computingdeep learning

Soft Skills

teamworkcommunicationanalytical abilitiesresults-focused

Certifications

BS in EngineeringBS in MathematicsBS in PhysicsBS in Computer ScienceMSPhD