Top Tech Jobs & Startup Jobs

Own product strategy and roadmap for an AI infrastructure capacity platform, covering resource planning, allocation, operational workflows, visibility, analytics, and adoption. Define features, metrics, dashboards, requirements, and acceptance criteria while partnering with engineering, operations, analytics, and product teams. Apply AI tools and prototyping methods to improve decision-making and user experience, and guide platform development through technical, operational, and scalability tradeoffs.

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.

Lead the optimization and performance analysis of distributed training and inference workloads on NVIDIA GPU platforms, with responsibilities including debugging, benchmarking, and ensuring reliability of large-scale AI systems.

Design, develop, debug, and validate low-level GPU power and performance-management software, including P-state and DVFS functionality. Collaborate across hardware, firmware, drivers, architecture, validation, and platform teams throughout the product lifecycle. Analyze workload, power, thermal, clock, voltage, and telemetry interactions; resolve cross-layer stability and reliability issues; support pre-silicon validation, silicon bring-up, production, automation, and technical documentation.

Leads research and engineering in compilers, programming languages, formal methods, and automated reasoning. Develops GPU and heterogeneous-computing compiler technologies, verified optimizations, program analyses, proof-generation techniques, and AI-assisted compiler tools. Collaborates with compiler, CUDA, GPU architecture, AI, systems, and research teams to transition prototypes into production. Mentors researchers and engineers while influencing NVIDIA’s compiler stack.

Leads engineering build activities for new NVIDIA products, coordinating multifunctional teams, prototype hardware planning, supplier and vendor interactions, resource allocation, risk management, logistics, testing, reporting, and prototype distribution. Ensures boards and systems are delivered with appropriate quality, configuration, timing, and quantity for development and testing. Improves build processes and infrastructure while supporting successful project releases into manufacturing.

Design, develop, verify, and maintain embedded system software and kernel drivers for NVIDIA Tegra ARM-based SoCs. Responsibilities include pre-silicon modeling, silicon bring-up, core OS enablement, hardware and software collaboration, unit testing, documentation, and system-level debugging. The engineer will also influence hardware architecture through design specifications and support next-generation SoC platforms.

Conduct fundamental research in generative AI, designing and implementing novel large-scale models for text, image, video, 3D, multimodal, or scientific applications. Publish original research, collaborate with research and product teams, present at conferences, and transfer innovations to product groups.

Lead development and optimization of local AI agent frameworks and runtimes for Windows PCs with NVIDIA GeForce RTX GPUs. Build secure, sandboxed, privacy-focused agent execution and inference systems, collaborate with AI research, driver, and open-source teams, and establish deployment guidelines. Mentor engineers while delivering production-ready code using Windows systems programming, C++, Python, LLM inference pipelines, GPU acceleration, and agent orchestration frameworks.

Lead security engineering for RTOS, hypervisor, and embedded virtualization: design and review defenses, collaborate on CPU/SoC security, perform threat modeling and automotive TARA, review low-level C/C++ code, build fuzzing and test infrastructure, assess vulnerabilities, and drive security fixes and verification toward automotive safety and security standards.