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.
NVIDIA is looking for an engineering leader who is hands-on with deep learning—comfortable reading/modeling code, not just running it. You bring strong intuition for modern architectures (e.g., transformers, diffusion, VLMs etc), deep experience tuning for NVIDIA GPUs (kernels, memory, latency/efficiency trade-offs) / SOCs, and a proven record 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 to experts in the industry is a great fit for this role!
What you'll be doing:
Lead, encourage, and develop world-class engineering teams distributed across various India locations.
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.
Performance Benchmarking: Orchestrate efforts to achieve leading performance results on industry benchmarks like MLPerf on various edge and Enterprise devices.
Technical Leadership & Influence: Function as a technical leader for deep learning across multiple teams, giving oversight and build support. Apply customer insights to influence the composition and structure of upcoming SOC / GPU deep learning hardware.
Scaling the team: Strategically hiring to meet new demands while also mentoring and adjusting existing teams to new deep learning challenges.
Representing Nvidia Deep learning solutions in webinars, conferences and partner events
What we need to see:
Masters in Computer Science/Electrical Engineering or equivalent experience.
A minimum of 8 years of meaningful involvement in machine learning/deep learning research or practical experience, coupled with 6+ years of leadership background and overall 12+ years of industry experience.
Over 10 years of validated expertise in the embedded software sector, holding technical leadership positions accountable for delivering outstanding production software within a multifaceted setting.
Deep Knowledge of GPU, CPU and dedicated deep learning architecture fundamentals and low-level performance optimizations using heterogeneous computing.
Hands-on experience with Multimedia Frameworks, Computer Vision, VLMs, LLMs, or multimodal AI systems applied to perception, data triage, or automated labeling.
Strong expertise in large-scale data processing, systems build, or machine learning pipelines.
Strong communication, careful planning, and technical leadership capabilities.
Ways to Stand Out from the Crowd:
We welcome candidates with a PhD or equivalent experience in a relevant field
Leadership role in production deployment of Smart Spaces, Physical AI with a deep understanding of constraints and advancements of sensing, computing, and model architecture evolutions.
Ability to lead and drive global teams across multiple continents and time zones
Deep experience with CV, LLMs, VLMs, GenAI Models, and standards.
With a competitive salary package and benefits, NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous director-level engineer who loves challenges? Do you have a genuine passion for advancing the state of Data Science across a variety of industries? If so, we want to hear from you!