Every listing shows a published salary. Filter by role, country, remote work or seniority. Updated 16h ago.
Generate real-time 3D world model utilized by planning, incorporating a variety of inputs from sensors and external sources. Enable HD mapless driving in complex urban scenarios by creating enriched BEV models of the world.
Taking responsibility for the workload and market approach for data analytics and data processing on NVIDIA data center CPUs — identifying priority workloads, customer scenarios, and the benchmarks and proof points that should guide the roadmap.
Together, we focus on how models behave in production, not just on benchmarks. Evaluate and improve Small Language Models used in GeForce G-Assist, with an emphasis on accuracy, robustness, and conversational reliability.
Embedded SRAM design: Transistor-level circuit design, supervising layout implementation, physical and logical verification, and debug of SRAM macros.
Lead, hire, mentor, and grow a high-performing team of engineers building employee-facing products software development, CI/CD, and agentic AI experiences.
Design, develop, test, debug, and optimize GPU firmware throughout the entire GPU lifecycle. Continuously evaluate and improve the security posture of firmware and hardware that form the root of trust for our products.
Collaborate with senior leaders to develop product strategies and development plans for datacenter products and power solutions. Own programs from concept and design through bring-up, validation, mass production and sustaining.
Designing end-to-end solutions for Prediction and AV stack using state of the art ML techniques to enable agents prediction across various driving environments from complex intersections to rural curvy roads to multi-level highways.
Support technical engagements with OEM and deployment partners, helping to understand their workloads and identify how NVIDIA's technology stack can address their needs, under the guidance of senior team members.
Understand, modify, and improve an NVIDIA proprietary GPU compiler backend written in C++. Design and develop new compiler passes and optimizations to produce best-in-class, robust, supportable compiler and tools.
Lead the development and maintenance of validation plans, detailed test procedures, and supporting documentation for L6, L10, and L11 products.
Co-design future architectures for NVIDIA's data processing platforms, targeting performance, efficiency, and cost.
Develop and maintain verification infrastructure, including testbenches, BFMs, checkers, monitors, scoreboards, assertions, and constrained-random stimulus.
Developing diagnostic and stress software in C/C++ and Python for complex hardware systems. Interfacing with hardware blocks, firmware, Linux device drivers, registers, telemetry, and low-level debugging tools.
Help shape the narrative around datacenter AI and our platform capabilities. Help members of the media understand how advances in NVIDIA technology are having an impact across industries.
Serve as a trusted advisor who understands complex or large-scale customer workloads and maps them to NVIDIA’s technology stack to achieve measurable outcomes.
Design, build and operate hosted Spark service control plane on Kubernetes: the Java REST API, the Spark Connect runner, Kyuubi, and deployment using Helm charts and Flux. Own code review for one or more services end to end and keep them releasable on the release train.
Develop and lead influencer relation activities that showcase how open-source NVIDIA Nemotron models are advancing AI for the industry. Showcase how NVIDIA model research is deepening understanding of AI and pioneering new technologies.
Build shared self-service and validation mechanisms that let engineering teams configure and use supported infrastructure workflows with less manual assistance.
Partner with energy-sector customers, ISVs, and account teams on discovery, architecture reviews, technical deep dives, POCs, benchmarks, demos, and production deployment guidance for AI infrastructure.
Design and implement efficient GPU code generation techniques in TensorRT that balance generated code performance, compilation overhead, and startup latency.
Today, visual computing is becoming increasingly central to how people interact with technology, and there has never been a more exciting time to join our team. We provide the hardware, infrastructure, and hands-on technical support that brings every experience to life.
You will be working on architecting GPU power features and system level power management solutions for NVIDIA products.
Be involved in the security architecture of NVIDIA Networking firmware — trust boundaries, privilege separation between firmware domains, device identity and key storage, secure boot and chain of trust, and secure update and anti-rollback flows.
US, USA