Currently tracking 440 active AI roles, down 53% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $100k–$575k (avg $262k).
NVIDIA currently has 496 active AI-related job listings. The majority of these roles, 52%, are focused on serving infrastructure, with agents representing another significant segment at 23%. Engineering is the dominant function, with 441 positions. The United States leads hiring geographies with 287 roles, followed by China with 64. Frequent tech tags include model_serving, inference_infra, and agent_orchestration, suggesting a focus on deployment and management of AI models. Over the last 30 days, NVIDIA posted 214 new AI roles, a 27% decrease compared to the previous 30-day period.
NVIDIA currently has 487 active AI-related roles in our index. The most common open titles are: Deep Learning Performance Architect (4), Senior Deep Learning Performance Architect (4), AI Research Scientist (3), Developer Technology Engineer - AI (3), Manager, Deep Learning Algorithms (3). Most positions are in Engineering and Research.
NVIDIA's active AI hiring is concentrated in: serving infrastructure (54%), agents (21%), application (8%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
NVIDIA is hiring AI talent in: United States (286 roles), China (59 roles), Israel (50 roles), Germany (21 roles).
Job postings at NVIDIA most frequently reference: model serving, inference infra, agent orchestration, llm observability, multimodal.
In the past 30 days, NVIDIA has posted 110 new AI-related roles. That is a -50% change versus the prior 30 days (218 → 110).
| Title | Stage | AI score |
|---|---|---|
| AI Workload and Networking Research Architect Research Architect role focused on optimizing AI workloads and networking infrastructure for NVIDIA's AI computing platforms, involving modeling, analysis, and influencing future product roadmaps. | ServePost-train | 9 |
| Senior Software Architect, AI Networking NVIDIA is looking for a Senior Software Architect to design and optimize inference infrastructure for large language models running on GPU clusters. The role involves working across software and hardware domains to define deployment and scaling strategies, optimize latency and throughput, and collaborate with various teams to ensure high-performance solutions. | Serve |
| 9 |
| Senior Software Architect, AI Networking Senior Software Architect role focused on designing and optimizing large-scale LLM inference infrastructure on GPU clusters, involving system-level optimizations for latency, throughput, and cost-efficiency. | Serve | 9 |
| Senior Software Research Architect, AI Networking NVIDIA is seeking a Senior Software Research Architect to improve the framework for large-scale LLM learning and prediction. This role focuses on designing and optimizing systems for generative AI workloads on advanced GPU clusters, specifically leveraging the NVIDIA Spectrum-X Networking Platform to define deployment and scaling strategies. The architect will work on inter-node communication, compute scheduling, and system-level optimization, collaborating with engineers and researchers to enable generative AI technologies in real-world applications. | ServePretrain | 9 |
| Software Engineer, AI Networking Architect NVIDIA is seeking an AI Networking Architect to optimize AI workload performance by analyzing AI models, distributed training, and inference workloads, and translating research insights into software, hardware, and networking architecture requirements. The role involves building platforms and simulations to evaluate trade-offs and influence future NVIDIA product roadmaps. | ServeAgent | 8 |
| Senior Solutions Architect - Deep Learning Senior Solutions Architect focused on Deep Learning and Agentic AI tools, collaborating with customers to build solutions using NVIDIA technology. Responsibilities include technical sales support, integrating NVIDIA tech into HPC, championing Deep Learning internally, and developing demo solutions. | ServeAgent | 8 |
| Senior Software Engineer, Deep Learning Inference Senior Software Engineer focused on optimizing deep learning inference for LLMs and omnimodal architectures on NVIDIA hardware, including GPU kernel tuning, distributed inference, and contributing to open-source libraries. | Serve | 8 |
| Senior Hardware Architect, Deep Learning GPU and System Senior Hardware Architect role focused on designing next-generation GPUs and systems to advance the state of AI, analyzing deep learning workloads, and proposing new features for acceleration. Requires 8+ years of experience in performance, hardware architecture, and deep learning analysis. | Serve | 8 |
| Senior Performance Engineer - LLM Inference Frameworks NVIDIA is seeking a Senior Performance Engineer to optimize LLM inference infrastructure on GPUs, focusing on throughput, memory efficiency, and scalability. The role involves designing and implementing high-performance pipelines, profiling, tuning model execution, and innovating techniques like Speculative Decoding and quantization. Experience with deep learning frameworks and performance debugging is required. | Serve | 8 |
| Senior AI Software Development Engineer, TensorRT-LLM NVIDIA is seeking a Senior AI Software Development Engineer for its TensorRT-LLM team. The role involves crafting and developing robust, scalable inference software for LLMs, focusing on performance analysis, optimization, and tuning. The engineer will write high-quality C++/Python code for the core backend software and collaborate with various teams to guide deep learning inference direction. A strong background in software development, LLM inference techniques, and deep learning frameworks is required. | Serve | 8 |
| Senior AI Developer Technology Engineer Senior Developer Technology Engineer focused on researching and developing techniques to GPU accelerate AI workloads, optimizing performance on modern CPU and GPU architectures, and collaborating with the developer community and internal teams to influence next-generation hardware and software design. | Serve | 8 |
| Senior High-Performance System Architect NVIDIA is seeking a Senior High-Performance System Architect to define and research NVL system architecture for large-scale, high-performance computing clusters used to train advanced AI models. The role involves working across algorithms, software, firmware, and hardware, collaborating with cross-functional teams, and analyzing simulation results. | ServePretrain | 8 |
| Senior Software Architect, Advanced Development Senior Software Architect focused on accelerating networking and building AI data centers, researching transport functions for AI workloads, and leading architectural efforts in distributed AI, deep learning, HPC, SDN, virtualization, and storage. | Serve | 8 |
| Senior AI Storage Software Architect NVIDIA is seeking a Senior AI Storage Software Architect to define and design the next generation of storage solutions for AI workloads, including training, inferencing, KV cache, and RAG. The role involves researching AI storage workloads, optimizing them, designing the storage software stack and APIs, leading POCs, and driving hardware features for DPUs and NICs. Requires 5+ years of storage experience and familiarity with AI applications and technologies. | ServeData | 8 |
| Senior Networking Performances Architect NVIDIA is seeking a Senior Networking Performances Architect to shape the future of high-performance and ML/AI computing. This role will analyze network feature performance for AI workloads on large-scale HPC clusters, develop network behavior models, and generate insights for next-generation products. The ideal candidate will have a strong background in system engineering/architecture, performance research, Python, and a good understanding of AI models and large-scale networks. | Serve | 7 |
| Senior HPC and AI Operation Engineer NVIDIA is seeking a Senior HPC and AI Operation Engineer to manage and maintain large-scale HPC/AI clusters, including job scheduling, CI/CD pipelines, and troubleshooting from bare metal to application level. The role involves supporting R&D activities and engaging in POCs, requiring strong Linux administration, scripting, and knowledge of HPC/AI technologies, storage, and networking. | Serve | 7 |
| Senior Software Engineer, Data Center Workloads – Infrastructure Senior Software Engineer focused on developing and executing software-driven characterization workflows for AI workloads on NVIDIA rack-scale systems. The role involves analyzing, characterizing, and optimizing power, performance, and drive behavior across the full stack, including GPUs, CPUs, networking, and system software. Key responsibilities include building automated frameworks for data collection and analysis, investigating system behavior, and supporting new platform bring-up. | Serve | 7 |
| Senior Performance Engineer Senior Performance Engineer at NVIDIA focusing on optimizing AI and HPC workloads on GPU/CPU clusters. Responsibilities include profiling, benchmarking, identifying bottlenecks, and developing performance analysis tools, with a strong emphasis on high-performance networking and telemetry. | Serve | 7 |
| Senior Software Engineer - Verification AI Infrastructure Senior Software Engineer focused on building and optimizing scalable software automation systems with AI/ML integration for NVIDIA's Data Center environments. The role involves developing automation and validation tools, improving system performance, and troubleshooting complex issues in distributed systems. | Serve | 7 |
| Senior Software Solutions Architect - NVIS Senior Software Solutions Architect at NVIDIA, focusing on helping customers deploy and integrate NVIDIA's AI and machine learning software stacks (like NVIDIA AI, Run:ai, Mission Control) into their existing MLOps environments. This involves collaborating with infrastructure admins, data scientists, and ML engineers, developing integration scripts, diagnosing performance issues, and improving deep learning model performance within cloud-native environments. | Serve | 7 |
| Manager, AI Networking Performance Research and Analysis Manager for AI Networking Performance Research and Analysis at NVIDIA, focusing on optimizing networking technologies (NIC, Switch) for AI workloads like LLM training and inference. The role involves end-to-end performance strategy, from pre-silicon modeling to GA, and building telemetry frameworks and dashboards for performance tracking and root cause analysis. Requires strong experience in high-performance networking, cluster performance, and managing engineering teams, with a focus on Python, Bash, and C/C++. | ServeAgent | 7 |
| Senior Networking Solution Test Engineer Senior Networking Solution Test Engineer at NVIDIA focusing on Ethernet-based AI clusters. Responsibilities include designing test requirements, building testbeds, owning end-to-end cluster troubleshooting, debugging networking components (NCCL, RoCE/RDMA), defining tests for automation, running regression/performance/functional/scale testing, and profiling deep learning workloads. Requires 5+ years of Linux networking/system-level testing, strong debugging skills, expertise in NIC validation, and knowledge of AI networking libraries and protocols. | Serve | 7 |
| Senior System Software Architect, AI and GPU Networking This role focuses on architecting and optimizing NVIDIA's GPU Networking offerings for AI workloads, including distributed AI, deep learning, inference, and model serving. It involves co-designing hardware features and leading the architecture and development of new technologies and runtime systems for AI data centers. | ServePost-train | 7 |
| Senior AI Networking System Architect NVIDIA is seeking a Senior AI Networking System Architect to define and develop the architecture for next-generation NVL systems that power large-scale high-performance computing clusters for AI research and various industries. The role involves end-to-end system architecture, research across algorithms, software, firmware, and hardware, and developing simulation models for performance testing. | Serve | 7 |
| Senior VLSI CAD and AI Automation Engineer Senior Engineer to develop and integrate AI/ML solutions for VLSI design automation, focusing on improving workflows, deploying algorithms, and maintaining automation infrastructure. Requires strong Python, AI/ML framework experience, and knowledge of VLSI physical design and EDA tools. | Serve | 7 |
| Senior Software Advanced Developer Develop and prototype advancements in distributed training and inference using NVIDIA's Spectrum-X AI fabric, focusing on improving AI app-networking connections through communication refinement, congestion control, NIC firmware coding, and switch SDK features to enhance AI factory efficiency and large-scale AI system development, scaling, and speed. | ServePretrain | 7 |
| Director, Software Architecture NVIDIA is seeking a Director of Software Architecture to lead the development of AI data centers and networking technologies. The role involves identifying and evaluating new technologies, leading the development of new networking applications using data plane programming, engaging with customers, defining a strategic vision, and managing technical teams. Requires an M.Sc. or PhD., 12+ years of software architecture experience, 8+ years of management experience, and expertise in AI inference algorithms, frameworks, and systems. | Serve | 7 |
| Software Architect, Advanced Development Research role focused on the intersection of Networking, Security, and Communications, with a specific emphasis on applying AI to these domains. The role involves technical leadership, architecture design, SDK development for new hardware, and implementing services. A key aspect is working with AI-powered networking machines. | Serve | 7 |
| Senior Software Architect - Deep Learning and HPC Communications Senior Software Architect role at NVIDIA focusing on designing and implementing next-generation data center platforms and scalable communication software for AI and HPC workloads. The role involves investigating performance bottlenecks, exploring innovative HW/SW solutions, building proofs-of-concept, and using simulation to evaluate large GPU cluster performance. | Serve | 7 |