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 |
|---|---|---|
| Deep Learning Performance Architect NVIDIA is seeking a Deep Learning Performance Architect to analyze, model, and optimize deep learning system performance, particularly for LLM workloads, on state-of-the-art hardware architectures. This role influences future hardware and software design by collaborating with various internal teams. | Serve | 9 |
| Deep Learning Performance Architect NVIDIA is seeking a Deep Learning Performance Architect to optimize deep learning hardware and software architectures for edge devices, workstations, and data center GPUs. The role involves benchmarking, performance modeling, bottleneck identification, and exploring new hardware/software capabilities, with a focus on LLMs and generative AI. Experience with AI agents for engineering workflows is also mentioned. | ServePost-train |
| 9 |
| Deep Learning Performance Software Engineer Develops GPU-accelerated deep learning software, including compilers, DSLs, and optimized kernels, for current and next-generation chips, focusing on performance analysis of AI workloads and integration with AI frameworks. | Serve | 9 |
| AI Computing Architect NVIDIA is seeking an AI Computing Architect to develop innovative architectures for deep learning performance and efficiency, analyze trade-offs using models and simulators, and prototype algorithms. The role requires strong programming skills, computer architecture background, and a foundation in machine learning. | ServePost-train | 9 |
| AI Computing Software Development Engineer, LLM Inference Software Development Engineer focused on LLM inference software (TensorRT LLM and TensorRT Edge LLM) at NVIDIA, involving crafting, scaling, performance analysis, optimization, and tuning of inferencing software for GPUs. The role requires strong C/C++ skills, experience with deep learning frameworks, and collaboration across teams. | Serve | 8 |
| AI Computing Software Development Engineer, TensorRT NVIDIA is seeking an AI Computing Software Development Engineer for its TensorRT team to craft and develop robust, scalable inferencing software for GPUs. The role involves performance analysis, optimization, tuning, and collaborating with various teams to guide the direction of machine learning inferencing. Requires a Masters or higher degree, 2+ years of software development experience, strong C/C++ skills, and familiarity with deep learning frameworks. | Serve | 8 |
| AI Computing Development Engineer, TensorRT and TensorRT-LLM AIGV NVIDIA is seeking software engineers to develop and optimize inferencing software (TensorRT/TensorRT-LLM) for AI computing. The role involves performance analysis, tuning, integrating AI advancements, and collaborating across teams to shape machine learning inferencing on NVIDIA platforms. Requires strong programming skills, experience with deep learning frameworks, and a proactive approach. | Serve | 8 |
| Developer Technology Engineer - AI NVIDIA is seeking an AI Developer Technology Engineer to study and develop cutting-edge deep learning techniques, analyze and optimize performance on GPU architectures, and work with customers to provide AI solutions using GPUs. The role involves close collaboration with internal NVIDIA teams to influence future architectures and software platforms. | Serve | 8 |
| AI Computing Development Engineer, TensorRT and TensorRT-LLM NVIDIA is seeking software engineers to develop and optimize AI inference software (TensorRT/TensorRT-LLM) for GPUs. The role involves performance analysis, tuning, integrating new advancements, and collaborating across teams to shape the future of machine learning inferencing. | Serve | 8 |
| Senior DGX Cloud AI Infrastructure Software Engineer NVIDIA is seeking a Senior DGX Cloud AI Infrastructure Software Engineer to design, build, and maintain AI infrastructure for large-scale AI training and inferencing. The role involves optimizing efficiency and resiliency of AI workloads, developing scalable AI and Data infrastructure tools, and ensuring high availability of AI systems. | ServeData | 8 |
| AI Computing Development Engineer, TensorRT-LLM NVIDIA is seeking software engineers to develop and optimize inferencing software for AI models, specifically focusing on TensorRT-LLM. This role involves performance analysis, tuning, and collaboration across teams to advance machine learning inferencing capabilities. | Serve | 8 |
| Developer Technology Engineer - AI NVIDIA Developer Technology Engineer focused on optimizing AI workloads, particularly large language models (LLMs), on NVIDIA's GPU platform. The role involves deep dives into application performance, GPU kernel optimization, distributed training and inference, and collaboration with various internal teams and external developers. It requires strong software engineering skills, parallel programming expertise, and a focus on performance analysis and tuning. | ServePost-train | 8 |
| System Software Architect, AI and GPU Networking NVIDIA is seeking a System Software Architect to research and develop advanced networking solutions for AI data centers, focusing on accelerating AI workloads, inference, and model serving. The role involves enhancing GPU networking offerings, designing optimizations for data movement, and evaluating new technologies. | ServePost-train | 8 |
| Senior Manager, Deep Learning Performance Architecture NVIDIA is seeking an Engineering Manager to lead a Deep Learning Performance Architect Team. This role involves managing a team focused on analyzing deep learning networks and advancing deep learning computing systems through hardware/software co-design. Responsibilities include establishing team objectives, collaborating with software framework and hardware architecture teams, characterizing deep learning workloads, performance tuning, optimizing software stacks, and driving the evolution of next-generation hardware and software architectures. | Serve | 8 |
| Deep Learning Performance Architect NVIDIA is seeking Software Engineers to join their Deep Learning Inference team, focusing on developing and optimizing GPU-accelerated deep learning kernels for inference. The role involves performance analysis, tuning, and collaboration with cross-functional teams on innovative solutions. | Serve | 8 |
| Senior System Software Architect, HPC and AI Networking NVIDIA is seeking a Senior System Software Architect to design and prototype scalable software systems for distributed AI training and inference, focusing on optimizing throughput, latency, and memory efficiency. The role involves developing and evaluating communication libraries, collaborating with AI framework teams, co-designing hardware features for AI acceleration, and contributing to runtime systems and protocol layers. | ServePost-train | 8 |
| Compute Architecture Software Engineer NVIDIA is seeking an LLM Inference Software Engineer to accelerate LLM inference using GPU technology on the TRTLLM project. The role involves developing and optimizing software solutions, implementing GPU-based algorithms, and improving performance across diverse computing environments. | Serve | 8 |
| Deep Learning Performance Architect, CUTLASS DSL NVIDIA is seeking an engineer to develop and optimize CUTLASS DSL, a Python-native language for GPU kernel development, and its associated MLIR dialects and lowering passes. The role involves accelerating kernel compilation for NVIDIA's next-generation AI platforms, aiming for performance comparable to CUTLASS C++. | Serve | 7 |
| Deep Learning Performance Architect NVIDIA is seeking a Deep Learning Performance Architect to optimize deep learning hardware and software architecture, analyze performance of deep learning algorithms on different architectures, identify bottlenecks, and explore new features and hardware capabilities. Requires a strong background in computer architecture and experience with deep learning platforms and frameworks. | Serve | 7 |
| Deep Learning Compiler Engineer - CUDA NVIDIA is seeking a Deep Learning Compiler Engineer to design and implement DSLs and compiler cores for emerging GPU architectures, focusing on optimizing performance for AI/LLM workloads and integrating with AI/ML frameworks. | Serve | 7 |
| Developer Technology Engineer, AI NVIDIA Developer Technology Engineer focused on optimizing AI and deep learning applications on GPU architectures, working with customers to provide AI solutions, and collaborating with internal teams to influence future hardware and software design. | Serve | 7 |
| Senior System Software Engineer - AI Performance and Efficiency Tools NVIDIA is seeking a Senior System Software Engineer to develop tools for AI researchers and SW/HW teams running AI workloads on GPU clusters. The role involves building internal profiling, analysis, debugging, benchmarking, and simulation tools to improve the performance and efficiency of AI workloads and systems. This includes partnering with HW architects and understanding deep learning frameworks, distributed training/inference, and GPU cluster technologies. | ServeData | 7 |
| Developer Technology Engineer – AI NVIDIA Developer Technology Engineer focused on optimizing deep learning and machine learning workloads on NVIDIA's accelerated computing platform (GPU, CPU, DPU) for key customers. Requires strong C/C++ and CUDA experience, with an MS/PhD in CS or related field. | Serve | 7 |
| Senior Computer Vision and Deep Learning Hardware Architect NVIDIA is seeking an Autonomous Vehicle Performance Architecture Engineer to design, model, and verify state-of-the-art programmable vision accelerators (PVA) for automotive and robotics. The role involves optimizing software for autonomous driving solutions, analyzing and prototyping applications, building performance models for future architectures, and collaborating with teams to enhance PVA architecture. Requires a Masters/PhD, 3+ years of relevant experience, strong C/C++ and computer architecture skills, and performance modeling/optimization expertise. Experience in DSP programming, autonomous vehicle software, deep learning, computer vision, and self-driving cars is a plus. | ServePost-train | 7 |
| Senior Software Engineer, NCCL Senior Software Engineer role focused on designing, implementing, and maintaining highly-optimized communication runtimes for Deep Learning frameworks and HPC programming interfaces on GPU clusters. This involves system software development, parallel programming interface contributions, and proof-of-concept creation for new designs and hardware features. | Serve | 7 |
| Senior Deep Learning Test Development Engineer, SDET Senior Deep Learning Test Development Engineer (SDET) at NVIDIA's AI SWQA team, responsible for validating the robustness and performance of NVIDIA's AI software and GPU Infrastructure across various AI scenarios. The role involves test planning, design, execution, automation, and bug management, with a focus on improving workflow processes and efficiency. Experience with LLM inference frameworks and AI development tools is required. | Serve | 7 |
| Senior System Software Architect, AI and GPU Networking This role focuses on architecting and enhancing NVIDIA's GPU Networking offerings to accelerate AI workloads, including distributed AI, deep learning, inference, and model serving. It involves co-designing hardware features and leading the architecture and design of new technologies for AI data centers. | ServePost-train | 7 |
| Senior Developer Technology Engineer This role focuses on optimizing GPU-accelerated code for training and inference performance of large-scale recommender systems. It involves designing and implementing high-performance C++/CUDA components, developing tests, and optimizing data flows between GPUs, NICs, and SSDs. The ideal candidate has experience with C++, CUDA, Python, GPU performance profiling, and ideally, building or optimizing recommender systems or production ML workloads on GPUs. | ServeShip | 7 |
| HPC and AI Cluster Engineer NVIDIA is seeking an HPC and AI Cluster Engineer to manage and maintain large-scale HPC/AI clusters, including Linux job scheduling, CI/CD pipelines, and troubleshooting from bare metal to application level. The role involves supporting R&D activities and POCs, working with cutting-edge hardware and software, and collaborating with researchers and customers to develop solutions. | Serve | 7 |
| GPU Computing Engineer - Autonomous Driving NVIDIA is seeking a GPU Computing Engineer in Shanghai to analyze Deep Learning models and investigate TensorRT stability and performance issues. The role involves working with a global team on CUDA and TensorRT development, extracting feature requirements, and generating documentation. Requires strong C/C++/Python skills, knowledge of inference networks, and experience with deep learning frameworks like PyTorch. | Serve | 7 |
| Deep Learning Performance Software Engineer NVIDIA is seeking a Deep Learning Performance Software Engineer to develop GPU-accelerated deep learning software, focusing on optimizing deep learning kernels and end-to-end performance through tile-based GPU programming. The role requires strong C/C++ skills, GPU programming experience (CUDA or OpenCL), and performance modeling/optimization knowledge. | Serve | 7 |
| Senior DGX Cloud AI Infrastructure Software Engineer Senior Software Engineer role focused on building and integrating AI infrastructure for DGX Cloud, enabling developers to access GPU-optimized virtual machines. Responsibilities include crafting IaaS API integrations, developing a two-sided marketplace, and improving testing and observability for scalable, fault-tolerant solutions. | Serve | 7 |
| Developer Technology Engineer – AI NVIDIA Developer Technology Engineer focused on optimizing core parallel algorithms and data structures for GPUs, collaborating with application developers and internal NVIDIA teams to improve application performance and developer efficiency. Requires strong programming skills in C/C++/Python, parallel programming experience (CUDA), and mathematical fundamentals. | Serve | 5 |
| Senior Deep Learning Test Development Engineer, SDET Senior Deep Learning Test Development Engineer (SDET) at NVIDIA, focusing on validating the performance and robustness of Deep Learning software and GPU infrastructure across various AI applications like autonomous driving, healthcare, and NLP. The role involves test plan design, execution, automation, bug management, and leveraging AI-powered tools for efficiency. | Serve | 5 |
| Networking Solution Test Engineer - AI IB and Ethernet Cluster Debugging NVIDIA is seeking a Networking Solution Test Engineer to join their End-to-End Verification team. The role involves working on cutting-edge Ethernet-based AI clusters, debugging complex issues across hardware, system software, and AI workloads. Responsibilities include designing test requirements, building testbeds, owning end-to-end cluster troubleshooting, collaborating with development teams on networking components, defining tests for automation, running regression and performance tests, and profiling deep learning workloads. | Serve | 5 |