Top Tech Jobs & Startup Jobs

Supports and root-causes complex customer issues involving NVIDIA networking and AI cluster technologies. Develops bug fixes, workarounds, diagnostic tools, and performance-tuning recommendations in collaboration with R&D and support teams. Works with InfiniBand, NVLink, Spectrum-X, and high-performance lossless networks, analyzing logs, traces, metrics, and source code. Provides customer support and may work occasional weekends or holidays.

Design, implement, and operate large-scale observability and telemetry platforms focused on performance, reliability, monitoring, logging, and alerting. Manage services throughout their lifecycle, including system design, deployment, capacity planning, automation, incident response, and postmortems. Build infrastructure tools and frameworks for private and public cloud systems, improve availability and latency, and participate in on-call support for production environments.

Leads the development and production deployment of deep learning perception systems for autonomous vehicles. Manages engineering managers, researchers, and software engineers; directs architectures for multi-sensor fusion and real-time 3D world modeling; oversees the machine learning lifecycle from data generation through NVIDIA DRIVE deployment; and partners across planning, mapping, hardware, and safety teams while ensuring automotive quality standards.

Develop and optimize GPU-accelerated deep learning inference software for LLMs, multimodal, and generative AI models. Contribute features to vLLM, SGLang, FlashInfer, and NVIDIA inference libraries; implement algorithms, tune performance across GPU architectures, and improve large-scale model serving. The role requires strong C/C++ software engineering, collaboration across framework teams, and expertise in profiling, debugging, performance modeling, GPU programming, or multi-GPU communication.

Contribute to power estimation models for GPUs, explore architecture for energy efficiency, analyze performance versus power, and employ machine learning for modeling power and performance metrics.

Conduct FEA modeling and simulation to evaluate stress, warpage, thermo-mechanical behavior, materials, and reliability in advanced semiconductor packages. Develop modeling methodologies, assess packaging technologies and process options, interpret results, mentor collaborators, and guide material selection, package builds, and manufacturing processes. Collaborate cross-functionally, document methods, and present findings.

Lead manufacturing support for data center AI accelerator boards, coordinate engineering, diagnostics, supply chain, and factory handover for NPI to mass production. Drive risk mitigation, process improvements, customer qualifications, budget tracking, and cross-functional alignment to ensure production ramp and issue resolution.

Provides technical enablement and onsite/offsite support for NVIDIA enterprise datacenter hardware. Collaborates with OEM customers through design, validation, production, bring-up, and debugging; reviews server architecture, thermal, mechanical, electrical, schematic, layout, and signal-integrity designs; resolves hardware, firmware, software, PCIe, GPU interconnect, and management issues; develops design guides and technical collateral; and tracks and reproduces bugs.

Lead co-design and build of production agentic and Generative AI systems with strategic ISV partners. Define objectives, prototype and ship RAG, multi-agent, long-horizon workflows on NVIDIA's stack, drive adoption, collaborate with Product/Engineering/Research, and influence product roadmaps. Ensure production inference, evaluation, observability, and enterprise deployment (MLOps/Kubernetes/Docker) with strong technical execution and partner-facing leadership.

Lead product-security strategy and delivery for NVIDIA Jetson, L4T, and JetPack across architecture, firmware, Linux, platform software, releases, vulnerability response, and customer deployments. Establish secure-by-design standards, conduct threat modeling and security architecture reviews, coordinate vulnerability remediation, support cybersecurity regulatory readiness, and develop security documentation such as SBOMs and white papers. Influence engineering, PSIRT, legal, compliance, customers, and partners while tracking security and release-readiness metrics.