Top Tech Jobs & Startup Jobs

Develop and deliver system-level IP and RTL to measure performance on GPUs/SOCs. Create and automate flows, run/debug RTL checks (CDC, clocks, resets, latency), implement RTL features, and collaborate with architects, designers, and software engineers to support projects and performance monitoring.

Lead floorplan design from early architecture through physical implementation for high-performance SoCs/CPUs/GPUs. Collaborate with cross-functional teams to optimize area, power, timing, and interconnect; develop AI-driven workflows and tools; identify technical risks and drive mitigation to meet product goals.

Design, implement, and operate large-scale, high-performance storage clusters for AI/ML workloads. Develop monitoring, alerting, automation, and capacity management. Optimize latency, throughput, caching, compression, deduplication, tiering, and data placement. Support lifecycle from design to production, participate in on-call rotations, incident response, and continuous improvement with AI-driven automation and predictive analytics.

Lead design and development of diagnostics and validation systems for NVIDIA data center server platforms. Drive platform bring-up, hardware validation strategies, root-cause analysis, and diagnostic software across ODMs, CSPs, and field operations. Provide technical leadership, mentor teams, and define diagnostic architecture and roadmaps to ensure reliability and performance at scale.

Sell NVIDIA solutions to AI-native startups by building relationships, qualifying opportunities, forecasting, collaborating with solution architects and channel partners, and closing deals. Drive quota attainment while positioning NVIDIA CUDA-X and supporting technical and go-to-market integrations.

Lead global product strategy and lifecycle for co-packaged optics, silicon photonics, and optical interconnect hardware. Define requirements and roadmaps, coordinate cross-functional teams (architecture, ASIC, systems, software), engage hyperscalers and customers, and present strategy to executive leadership to drive next-generation datacenter networking products.

Lead architecture and global strategy for large-scale, low-latency distributed AI inference. Design high-throughput model serving, hardware-software co-optimization, orchestration for deployment/versioning/auto-scaling across cloud and datacenters, collaborate with customers and open-source ecosystems, and drive full software and system lifecycle for production reliability and performance.

Lead NCP and ISV business development for DGX Cloud and DSX OS: identify and prioritize partners, negotiate and manage agreements, coordinate cross-functional teams, drive technical integrations, build joint business plans, and convert partnerships into measurable customer deployments and revenue.

Lead architecture and development of production-grade Kubernetes platform capabilities: cluster management, control plane services, fleet lifecycle, provisioning, upgrades, remediation, and automation. Drive technical strategy, cross-team execution, operational reliability, and mentor senior engineers to improve scalability and operability for large-scale AI deployments.

Perform high-speed, high-density PCB layout from component placement through constraints and topology, ensuring signal and power integrity. Produce artwork/ODB++, test reports, and PCB documentation. Ensure designs meet SI, EMI/RFI, IPC, FCC, UL and European regulatory requirements while collaborating with product engineers and troubleshooting complex layout issues.