Top Tech Jobs & Startup Jobs

Design and scale Kubernetes-native, GPU-accelerated cloud architectures for large-scale robotics simulation, synthetic data pipelines, training, and inference. Advise partners, optimize scheduling, storage, networking, and GPU utilization, and drive adoption of NVIDIA Physical AI frameworks while collaborating with product and engineering teams.

Lead end-to-end design, build, and operation of production enterprise AI systems embedded with business teams. Rapidly prototype, deploy, and measure AI solutions using LLMs, vector DBs, and Kubernetes, then productize reusable platform capabilities, ensure observability/CI/CD/security, and mentor engineers while driving enterprise adoption and measurable business impact.

Build and maintain scalable cloud-based PaaS/IaaS systems and CI/CD/release engineering tooling for DGX Cloud. Develop and improve deployment automation for on-prem and cloud, collaborate with cross-functional teams, support and document software, and enable reliable AI-focused platform operations.

Drive go-to-market strategy and partnerships for the semiconductor ecosystem to adopt NVIDIA software and hardware. Own GTM planning, sales enablement, pipeline generation, partner training, event strategy, cross-functional alignment, and deliver incremental revenue while providing product feedback and closing complex deals.

The Systems Quality and Reliability Engineer will manage RMA and FA debug processes, conduct tests, analyze quality data, and oversee hardware quality performance, collaborating with various engineers.

The Senior ASIC Design Engineer will design and implement RTL, analyze trade-offs, and collaborate on micro-architecture for GPUs and SoCs.

As an ASIC Verification Engineer, you will verify design and implementation of SoCs and GPUs, define verification scope, and collaborate with cross-functional teams.

Lead global partner marketing for NVIDIA's Enterprise ISV ecosystem: develop and execute co-marketing plans, demand-generation campaigns, events, content, and digital marketing; coordinate with Product, Sales, and BD; supervise execution and ROI, and build trusted partner relationships to amplify solutions on NVIDIA technology.

Design and implement idiomatic Python APIs and bindings for CUDA Core Libraries, develop and integrate native C/C++ components, define interoperability boundaries (Python, C/C++, Rust), optimize performance, own feature lifecycle (design through maintenance), and collaborate with compiler, runtime, and user teams to ensure correctness, usability, and performance.

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.