Director, Metropolis Accelerated and Inferencing Systems Software

Details

NVIDIA is a world leader in physical AI, powering self-driving cars, humanoid robots, intelligent environments, medical devices, and more. Our software platforms are at the core of this mission, enabling innovators to build world-changing products that save lives, improve working conditions, and elevate standards of living across the globe.

We are looking for an engineering leader who is hands-on with deep learning — comfortable reading and modeling code, not just running it. The role requires strong intuition for modern architectures (e.g., transformers, diffusion, VLMs), deep experience tuning for NVIDIA GPUs and SoCs (kernels, memory, latency/efficiency trade-offs), and a proven record delivering robust, low-latency inference at scale. You will lead teams that turn accelerated computing pipelines into reliable, measurable business impact for embedded and enterprise platforms and work with teams distributed across Europe, Asia, and the United States.

Responsibilities

• Lead, encourage, and develop world-class engineering and data teams distributed across Europe, Asia and the United States.
• Architect and operationalize NVIDIA’s end-to-end data inference acceleration strategy, powering inferencing 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 custom deep learning models and inference pipelines; offer direct customer support, including debugging, technical education, and handling customer inquiries.
• Draft and finalize Statements of Work (SOWs) with internal customers and partners.
• Orchestrate performance benchmarking efforts to achieve leading results on industry benchmarks like MLPerf on various edge and enterprise devices.
• Serve as a technical leader for deep learning across multiple teams; apply customer insights to influence SOC / GPU deep learning hardware composition and structure.
• Strategically hire, mentor, and scale teams to meet new demands and evolving deep learning challenges.
• Represent NVIDIA deep learning solutions in webinars, conferences, and partner events.

Requirements

• Master’s in Computer Science, Electrical Engineering, or equivalent experience.
• Minimum of 8 years of meaningful involvement in machine learning/deep learning research or practical experience, coupled with 7+ years of leadership background and overall 15+ years of industry experience.
• Over 10 years of validated expertise in the embedded software sector, with technical leadership accountability for delivering production software in complex environments.
• Deep knowledge of GPU, CPU and dedicated deep learning architecture fundamentals and 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.
• Strong expertise in large-scale data processing, systems build, and machine learning pipelines.
• Strong communication, careful planning, and technical leadership capabilities.

Ways to Stand Out

• PhD or equivalent experience in a relevant field.
• Leadership role in production deployment of smart spaces or physical AI with deep understanding of sensing, computing, and model architecture constraints and evolution.
• Proven ability to lead and drive global teams across multiple continents and time zones.
• Deep experience with computer vision (CV), LLMs, VLMs, GenAI models, and applicable standards.

Benefits and Additional Details

• Competitive base salary (range shown below) plus eligibility for equity and benefits.
• Base salary range: 320,000 USD - 488,750 USD (determined by location, experience, and pay of employees in similar positions).
• Applications accepted at least until January 17, 2026. This posting is for an existing vacancy.
• NVIDIA uses AI tools in its recruiting processes.
• NVIDIA is an equal opportunity employer and is committed to fostering a diverse work environment.