NVIDIA
Edge AI, Metropolis, and Blueprints (EMB)
Director,SystemSoftwareEngineering
Neural analysis suggests this role is
optimal for Director candidates.
“Director, System Software Engineering at NVIDIA. Skills: System Software Engineering, Deep learning, NVIDIA GPUs, Inference Acceleration, TensorRT, VLLM, VLMs, LLMs, multimodal AI systems. Lead, encourage, and develop world-class engineering and data teams decentralized across Europe, Asia, and the United States.. Architect and operationalize NVIDIA’s end-to-end data Inference Acceleration strategy, powering inference and continuous performance improvements.”
What You'll Achieve.
transform foundation models into real-time, GPU-accelerated video intelligence systems; scaling multimodal reasoning; enabling agentic development workflows; NVIDIA as the default platform for Physical AI; delivering robust, low-latency inference at scale; turn Accelerated Computing pipelines into reliable, measurable business impact; powering inference and continuous performance improvements; achieve leading performance results on industry benchmarks like MLPerf
Industry & Context.
debugging; technical leadership
What They're Looking For.
Must Have
Bachelor's and/or Master's in Computer Science/Electrical Engineering or equivalent experience, 15+ years of overall experience, 10+ years of significant involvement in machine learning/deep learning research or practical experience, 7+ years of leadership background, Over 10 years of validated industry expertise in the embedded software sector, technical leadership positions accountable for delivering outstanding production software within a multidimensional setting, Deep knowledge of GPU, CPU, and dedicated deep learning architecture fundamentals, low-level performance optimizations using heterogeneous computing, Hands-on experience with VLMs, LLMs, or multimodal AI systems applied to perception, data triage, or automated labeling, expertise in large-scale data processing, systems building, or machine learning pipelines, communication, careful planning, and technical leadership capabilities
Nice to Have
PhD in a relevant field such as Spatial Computing & Awareness, Sim-to-Real Transfer, Human-to-Physical AI Interaction, Deep experience with CV, LLMs, VLMs, GenAI models, and standards, Technical thought leadership in production deployment of Smart Spaces, Physical AI, with a deep understanding of constraints and advancements of sensing, computing, and model architecture evolutions, Current experience leading and driving global teams across multiple continents and time zones
What You'll Do.
and develop world-class engineering and data teams decentralized across Europe
and the United States.
Architect and operationalize NVIDIA’s end-to-end data Inference Acceleration strategy
powering inference and continuous performance improvements.
Drive strategic implementations of TensorRT
and other accelerated frameworks for inference solutions for Edge and Enterprise devices: Lead Accelerated Computing efforts and solutions for key Metropolis verticals.
Set up Proofs of Readiness (PORs) and guide their implementations.
Collaborate with major Metropolis OEMs and Partners to architect highly accelerated and optimized custom deep learning models and inference pipelines for their specific requirements.
Offer direct customer support
and handling customer inquiries for our Metropolis partner and customers.
Responsible for drafting and finalizing SOWs with internal customers and partners.
Orchestrate efforts to achieve leading performance results on industry benchmarks like MLPerf on various edge and Enterprise devices.
Function as a technical leader for deep learning across multiple teams
giving oversight and building support.
Apply customer insights to shape the composition and structure of upcoming SOC/GPU deep-learning hardware.
Strategically hiring to meet new demands while also mentoring and adjusting existing teams to new deep learning challenges.
Represent Nvidia Deep Learning solutions in webinars
How You'll Work.
Team & Collaboration
Lead, encourage, and develop world-class engineering and data teams decentralized across Europe, Asia, and the United States.; Collaborate with major Metropolis OEMs and Partners; Function as a technical leader for deep learning across multiple teams, giving oversight and building support.; Apply customer insights to shape the composition and structure of upcoming SOC/GPU deep-learning hardware.; mentoring and adjusting existing teams to new deep learning challenges.; Represent Nvidia Deep Learning solutions in webinars, conferences, and partner events
Communication Scope
communication; technical education; handling customer inquiries; Represent Nvidia Deep Learning solutions in webinars, conferences, and partner events
Process & Methodology
careful planning, Set up Proofs of Readiness (PORs) and guide their implementations., Orchestrate efforts to achieve leading performance results
Full Job Description
Within NVIDIA's Edge AI, Metropolis, and Blueprints (EMB), this team is the execution engine behind NVIDIA’s Vision AI strategy—owning the full lifecycle from model onboarding to production deployment. We transform foundation models into real-time, GPU-accelerated video intelligence systems using DeepStream and VSS. Our focus includes scaling multimodal reasoning and enabling agentic development workflows. We follow through between production data and model improvement. This work positions NVIDIA as the default platform for Physical AI. NVIDIA is looking for a proven Director of Systems Engineering who is hands-on with deep learning and comfortable reading/modeling code, not just running it. You bring strong intuition for modern architectures (e.g., transformers, diffusion, and VLMs); deep experience tuning on NVIDIA GPUs (kernels, memory, and latency/efficiency trade-offs)/SOCs; and a consistent track record of delivering robust, low-latency inference at scale. You have led teams that turn Accelerated Computing pipelines into reliable, measurable business impact for embedded and Enterprise platforms. You will work with a cohesive, high-performing team that’s been built and refined over the past nine years. An individual well-aligned with industry experts is a great fit for this role! **What You 'll be Doing:** * Lead, encourage, and develop world-class engineering and data teams decentralized across Europe, Asia, and the United States. * Architect and operationalize NVIDIA’s end-to-end data Inference Acceleration strategy, powering inference and continuous performance improvements. * Drive strategic implementations of TensorRT, VLLM, and other accelerated frameworks for inference solutions for Edge and Enterprise devices: Lead Accelerated Computing efforts and solutions for key Metropolis verticals. Set up Proofs of Readiness (PORs) and guide their implementations. * Collaborate with major Metropolis OEMs and Partners to architect highly accelerated and optimized c
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