Top Tech Jobs & Startup Jobs

Lead strategic GTM and co-selling initiatives with Google Cloud to drive NVIDIA AI adoption. Develop and maintain technical enablement assets, run developer activations and events, collaborate with Google Cloud field and engineering teams, convert samples into demos and labs, and translate customer feedback into product and roadmap insights.

Lead architecture and optimization of deep learning inference for autonomous driving platforms. Drive end-to-end performance analysis across models, compiler/runtime (TensorRT/Triton), CUDA kernels, memory and scheduling. Develop model optimization techniques (quantization, pruning, fusion), build profiling and benchmarking tools, and collaborate with platform, perception, safety, and silicon teams to deploy efficient, reliable DNNs on NVIDIA automotive compute platforms.

Lead validation of ML datacenter stacks from cluster to rack scale for CSPs: define test strategies, reproduce and triage customer bugs, validate fixes, run perf benchmarks, manage test data and tooling, produce release-readiness reports, and collaborate with internal and partner engineering teams.

Design and validate Ethernet networking fabrics for AI/HPC clusters; mentor customers; build demos/POCs; create reference architectures and training; collaborate with engineering, product, and sales to secure design wins and drive product feature development.

Design, develop, and debug system software for NVIDIA Halos across QNX, Linux, and hypervisor environments. Build BSPs, I/O virtualization, drivers, boot and diagnostics for mixed-criticality NVIDIA SoC platforms. Apply formal methods and safety standards (ISO 26262/21434), optimize platform bring-up, and implement debugging, tracing, logging, and performance-analysis solutions. Collaborate with ASIC, firmware, OS, safety, security, and platform teams.

Lead performance and scalability analysis of the Kubernetes-based accelerated runtime stack, design upstream control-plane changes for hyperscale clusters, optimize container startup and inference latency, advance confidential container performance, model large AI-factory deployments with simulations, build at-scale tests and monitoring, and collaborate with researchers and upstream communities to validate and publish results.

Lead a product marketing team to define and position NVIDIA laptop and embedded products, own messaging for OEM and channel partners, influence product/sales/marketing plans for new technologies, and train/align regional sales and marketing teams to drive product growth.

Lead product marketing for NVIDIACUDA and core acceleration libraries. Own positioning, messaging, and go-to-market for libraries and AI frameworks, translate technical features into developer-focused narratives, and build AI-driven PMM automation and assets.

Design and research next-generation data-center networking solutions spanning ASIC design, algorithms, topologies, routing protocols, and systems. Collaborate with internal teams, partners, standards bodies, and communities to develop networking technologies for AI and accelerated computing.

Lead architecture, implementation, and operation of highly available enterprise messaging and collaboration platforms (Exchange on-prem/hybrid/Online, SMTP/IMAP, Azure). Manage upgrades, patching, monitoring, security (SPF/DKIM/DMARC, anti-spam), migrations/tenant consolidations, and SaaS collaboration platforms. Provide incident diagnosis, mentor engineers, and drive automation and AI-enabled operational improvements.