Top Tech Jobs & Startup Jobs

Lead founding AI Safety & Security Engineering team, define harness architecture and engineering standards, drive Find/Validate/Patch roadmap, mentor engineers, and translate research into production-grade, secure ML systems.

Leads site reliability operations and Tier 3 IT support across identity, messaging, compute, endpoints, databases, networking, and datacenter infrastructure. Owns incidents, service quality, compliance, vulnerability remediation, asset management, root-cause analysis, automation, and permanent fixes. Provides technical leadership to site engineers, supports executives, coordinates with global platform teams and vendors, and represents site priorities in regional initiatives. Requires hands-on onsite work, on-call participation, and after-hours maintenance support.

This role focuses on driving adoption and alignment for ODM partners, supporting data center delivery, and incorporating partner feedback into product strategy.

Develop and formalize methods to validate reported vulnerabilities and generate/verify safe patches for internal NVIDIA targets. Define correctness, regression, and revalidation standards; produce repeatable, auditable processes and evidence. Apply AI-assisted workflows cautiously, perform bounded applied research on vulnerability classes, and document findings for independent security review.

Develop and maintain scalable build, regression, and release infrastructure for chip designers. Build user-facing services for scheduling, tracking, and triaging workflows, plus tools for collecting, analyzing, monitoring, and visualizing system metrics. Apply modern CI/CD practices, maintain reliable production-quality code, and support distributed computing, build systems, and software performance analysis.

Lead the development of AI-powered employee productivity experiences across web and mobile. Architect scalable services and UIs, integrate LLM and vector-search capabilities, connect HR and productivity platforms, and establish cloud-native engineering practices. Own system design, code reviews, observability, security, accessibility, and technical documentation while mentoring engineers and guiding cross-functional teams toward reliable global products.

Design and optimize agentic AI systems for NVIDIA’s CUDA ecosystem, including agent architectures, multi-agent workflows, tool use, memory, orchestration, training, verification, reward, and evaluation systems. Co-design AI systems across models, inference, compilers, runtimes, libraries, kernels, and GPUs. The role requires strong C/C++, Rust, and Python skills, GPU programming expertise, and experience with agent systems, reinforcement learning, or modern AI inference.

Design and deploy test methodologies for advanced NVIDIA silicon, including DFT architectures, ATPG verification, coverage analysis, pattern generation, and ATE bring-up. Partner with EDA vendors, CAD, VLSI, and product engineering teams to develop scalable test solutions. Lead complex scan-test lifecycles, support advanced chiplet and 3D designs, and mentor junior engineers.

Lead developer-focused performance optimization for RTX and DGX SoC platforms: collaborate with partners and internal teams to optimize CPU, AI, and 3D-graphics workloads, profile and debug CPU/GPU performance, influence next-gen SoC design, and mentor junior engineers. Occasional travel for conferences and partner site visits.

Develop Linux kernel and user-space power and thermal management software for NVIDIA Tegra and embedded platforms. Optimize performance, efficiency, latency, compute and memory utilization for edge AI and robotics workloads. Collaborate with hardware, software, and power architecture teams on platform estimation and optimization. Requires strong C, Linux, embedded systems, ARM, and system-level debugging experience.