Every listing shows a published salary. Filter by role, country, remote work or seniority. Updated 16h ago.
Build product positions - Collaborate with business leaders across NVIDIA to understand and communicate the value of our products to developers.
Designing and implementing cutting-edge techniques in the field of vehicle autonomy. Publish and present your original research, speak at conferences and events. Collaborate with other research team members, a diverse set of internal product teams, and external researchers.
Develop large-scale supervised learning and reinforcement learning training frameworks to support multi-modal foundation models for AVs capable of running on thousands of GPUs; Optimize GPU and cluster utilization for efficient model training and fine-tuning on massive datasets;
As a Senior Verification Engineer at NVIDIA, you will be responsible for verifying the design, architecture and micro-architecture using advanced verification methodologies.
You will work as part of a team to design and implement high speed interfaces and complex mixed-signal circuits using state-of-the-art sub-micron CMOS technologies and various EDA tools:
Design, develop and optimize server application responsible for managing NVLink networks of thousands of network devices! Collaborate with multiple teams in our multi-functional environment on developing new features and improvements.
We support multiple emulation environments using the latest emulation techniques (C/C++ DPI Transactors, SV assertions, Coverage, Power Estimation, SpeedBridges, Accelerated UVM Testbenches).
Introduce and integrate NVIDIA networking products with Hyperscalers. Build customers’ trust and understand their unique needs. Address sophisticated and obvious customer issues alongside engineering and support teams.
Conduct original research in the space of generative AI. Implement and train large-scale generative AI models for various content creation applications. Collaborate with other research team members, a diverse set of internal product teams, and external researchers.
As a member of the architecture team, you will be responsible for understanding how the GPU sub-system modules interoperate and interact with overall system.
Architecting and implementing high-performance communication and memory management libraries for distributed AI. Driving hardware-software co-optimization with GPU, DPU, NIC, and switch teams through GPUDirect RDMA, NVLink, and next-generation interconnects.
System/board level debug and validation of NVIDIA's products in fields like GPU cards, MGX servers, automotive, robotics, industrial PC, and consumer electronics to ensure the highest quality products reach the market.
Understand and analyze the potential vulnerabilities and risks in future systems for AI and AI-based systems. Develop creative hardware, software, and algorithms to enable trustworthy AI systems with strong and verifiable security, privacy, and safety guarantees.
Design new hardware features for future processing architectures targeted at deep learning workloads, for both training and inference. Advance the state of parallel computation. Be knowledgeable about future parallel programming models and their impact to hardware.
Collaborate with Sales Finance, Corporate Finance, Business Operations, and Manufacturing teams in leading a business unit’s financial performance from the perspective of product costs, inventory, and supply management.
You'll implement the design the industry’s leading processor for deep learning, gaming, and dedication computing. Responsible for validation of features on Silicon using hands-on lab equipment like logic analyzers etc.
Develop and ship performance-centric CUDA Driver features and programming-model capabilities from design through validation.
Develop novel architectures and system software implementations to enable scalable multi-GPU platforms. Understand and analyze the interplay between operating systems, CPU and GPU architectures, and efficient algorithm designs.
Responsible for building industry and AI insights into AI enablement and agentic development. Accelerate NVIDIA productivity by developing best state of the art AI systems. Produce tools, services, blueprints for NVIDIA AI developers.
Create products to help researchers and production model builders. Develop product strategy, roadmaps, and go-to-market plans. Collaborate with internal and external customers to build product-based roadmaps for training/post training software.
As a Verification Engineer at NVIDIA, you will be responsible for verifying the design, architecture and micro-architecture using advanced verification methodologies.
Technical leadership role to define/plan/implement/execute performance verification strategy of sophisticated CPU designs. Ability to delve into lowest level details of CPU unit design specification, implementation and it's performance impact.
Collaborate with NVIDIA Cloud Partners to create, implement, and deliver on NVIDIA's innovative hardware and software solutions.
Ensure all fixed assets are physically or systematically verified and aligned with the Company’s data center infrastructure management system and asset tracking systems.
US, USA