Top Tech Jobs & Startup Jobs

Partners with customers and internal teams to design, deploy, and optimize generative AI and LLM inference solutions. Develops proofs of concept, supports NVIDIA technology adoption, analyzes AI workload performance and power efficiency on Kubernetes, and advises developers, researchers, and data scientists. The role requires expertise in deep learning frameworks, GPU orchestration, MLOps, containerization, observability, and LLM inference, with occasional travel to conferences and customers.

Manages wafer supply plans, inventory positions, supply-demand tradeoffs, and executive reporting. Leads and mentors supply chain planners, collaborates with foundry partners to address shortages and forecast capacity, and aligns backend planning, engineering, and capacity teams to resolve bottlenecks. Drives continuous improvement and supports strategic planning in a global semiconductor manufacturing environment.

Lead customer and partner enablement for NVIDIA Embedded solutions from new product introduction through mass production. Define system requirements, architectures, specifications, documentation, and test plans. Collaborate with hardware, firmware, software, validation, sensor, AI, and project management teams to integrate solutions into automotive and robotic systems. Evaluate system performance, power efficiency, thermal and mechanical integration, and reliability while developing customer roadmaps and providing feedback for product improvements.

Leads the architecture, delivery, and operation of enterprise-scale agentic AI and automation platforms for IT operations. Builds and manages engineering teams, develops production AI agents and integrations, sets technical standards, owns roadmaps, and drives measurable improvements in cost, throughput, availability, SLAs, and compliance. Requires hands-on software engineering leadership, enterprise automation expertise, cloud and infrastructure proficiency, executive communication, and experience deploying governed autonomous workflows.

Designs and deploys large-scale NVIDIA AI and HPC GPU infrastructure for cloud partners and strategic customers. Leads technical engagements across the customer lifecycle, supports infrastructure development and production, builds networking and compute proofs of concept, troubleshoots performance and scaling issues, and delivers technical presentations and workshops. Partners with sales and business teams to identify opportunities and provides customer feedback to influence product strategy.

Lead semiconductor supply planners and own supply commitments for networking silicon products. Develop optimized production schedules across products and SKUs, balance capacity and material constraints, resolve supply-demand tradeoffs, guide substrate and material planning, support product ramps, analyze shortfalls, and present recommendations to senior management. Drive continuous improvement with internal teams and subcontractors across shipment performance, cycle time, and production efficiency.

Develop and implement manufacturing test solutions for datacenter systems, including test strategies, fixtures, equipment, diagnostic software, and automation infrastructure. Collaborate with contract manufacturers, investigate test technologies, review design-for-test considerations, and debug complex hardware and software issues during production builds. The role requires post-silicon validation experience, platform-level manufacturing testing, datacenter platform expertise, and Python and Bash programming.

Architect GPU boot, PCIe/CXL enumeration, and capability-discovery infrastructure. Collaborate with software, hardware, and verification teams to plan GPU features, develop C++ functional and performance models, create validation test plans, and support post-silicon validation. The role requires knowledge of computer and system architecture, with preferred experience in advanced interconnects, scripting, security constructs, encryption, RISC-V, and microcode development.

Manage and grow NVIDIA partner relationships in Manufacturing and Automotive: develop business plans, drive ecosystem enablement, increase adoption of NVIDIA AI solutions, maintain executive relationships, and present results in QBRs.

Design and develop low-level kernel drivers and embedded software for NVIDIA data center GPUs. Responsibilities include cross-platform Linux and Windows support, hardware initialization, device management, reset capabilities, telemetry, memory management, clock, thermal and power management, and performance optimization. The role collaborates with software, hardware, architecture, and OEM teams to support current products and develop next-generation GPU features.