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.
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 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 |
|---|---|---|
| Senior Deep Learning Software Engineer - Autonomous Vehicles Senior Deep Learning Software Engineer focused on developing and productizing deep learning solutions for autonomous vehicles. The role involves training, fine-tuning, optimizing perception DNNs, applying quantization, improving DNN architectures, and enhancing inference speed and power consumption. It requires strong programming skills, experience with deep learning frameworks, computer vision tasks, and familiarity with CNNs and Transformer architectures. Experience with low precision inference, quantization, and NVIDIA software libraries is a plus. | ServePost-train | 8 |
| Compiler Engineer - AI Inference NVIDIA is seeking an AI Compiler Engineer to optimize kernel generation and computational graph optimizations for AI inference and training workloads on next-generation GPUs. The role involves hands-on development, collaboration on hardware/software co-design, and scaling AI deployments in datacenters. |
| ServePost-train |
| 8 |
| Senior Software Engineer, Metropolis Vision AI Senior Software Engineer to develop and optimize high-performance Vision AI pipelines and large-scale distributed services for processing video, image, and 3D data. The role involves crafting real-time systems, developing multi-modal perception, using simulation/synthetic data, and profiling/tuning GPU-accelerated inference pipelines. Collaboration with research and platform teams is key, with an emphasis on bringing research into production at scale. | ServePost-train | 8 |
| Senior Software Engineer, AI Networking Senior Software Engineer role focused on building and productizing ML tools for optimizing AI workloads (LLM training/inference) across GPU/CPU clusters, with a focus on networking and system resource utilization. Involves distributed deep learning, ML-based optimization techniques, and performance analysis. | ServeAgent | 8 |
| Principal Deep Learning Communication Architect NVIDIA is seeking a Principal Deep Learning Communication Architect to lead the technical roadmap for communication libraries across next-generation platforms, ensuring seamless scaling of models to massive clusters. The role involves designing and optimizing communication primitives for heterogeneous interconnects, co-designing with application developers and silicon architects, and developing analytical models for system behavior. Expertise in parallel computing, HPC/distributed deep learning, inference engines, and GPU architecture is required. | ServeAgent | 8 |
| AI and FSI Developer Technology Engineer - New College Grad 2026 NVIDIA is seeking an AI and FSI Developer Technology Engineer to optimize AI and HPC workloads on NVIDIA GPUs and CPUs, focusing on performance tuning and eliminating bottlenecks for financial markets. The role involves research, development, analysis, and collaboration with experts to improve performance across the stack, from algorithms to kernels. The engineer will also publish and present their work and influence future hardware/software designs. | Serve | 8 |
| Senior Machine Learning Applications and Compiler Engineer, LPX Develops algorithms and optimizations for NVIDIA's LPX inference and compiler stack, focusing on mapping neural network workloads onto future NVIDIA platforms and optimizing end-to-end inference performance. Requires strong software engineering, compiler/runtime development, and deep learning framework experience. | Serve | 8 |
| Senior Software Engineer – TensorRT Edge-LLM Senior Software Engineer to develop and optimize a state-of-the-art inference framework for Large Language, Vision-Language, and Multimodal models on edge and embedded platforms, focusing on real-time performance and constrained environments. | Serve | 8 |
| Senior Performance Engineer - Deep Learning Senior Performance Engineer at NVIDIA focused on optimizing Deep Learning models and frameworks (PyTorch, JAX) for NVIDIA GPUs. The role involves building and supporting Transformer Engine, collaborating on systems research for performance improvements, implementing and benchmarking new DL models, contributing to MLPerf, and engaging with the open-source community and enterprise customers. It also involves influencing future hardware and software design. | ServePost-train | 8 |
| Senior Software Engineer, Quantized Inference Senior Software Engineer focused on optimizing quantized inference for LLMs by implementing recipes, developing kernels, and collaborating on inference engines like vLLM and TRT-LLM. The role involves model export pipelines, benchmarking, and data analysis tooling. | Serve | 8 |
| Senior Compiler Engineer, AI Inference Platforms NVIDIA is seeking a Senior Compiler Engineer to join its Deep Learning & AI Compiler (DLC) team. The role involves analyzing deep learning networks, developing compiler optimization algorithms, and collaborating with framework and architecture teams to accelerate AI inference performance on NVIDIA GPUs. The compiler is critical for data centers, personal devices, automotive, and robotics, focusing on inference performance, build time, memory footprints, and ease of use. | Serve | 8 |
| Senior AI Performance and Efficiency Engineer Senior AI/ML Performance and Efficiency Engineer focused on optimizing GPU cluster performance for AI/ML researchers by addressing infrastructure and application bottlenecks. This role involves building tools, analyzing efficiency, and collaborating across teams to improve hardware, software, and infrastructure usage for various ML workloads like Robotics, Autonomous vehicles, LLMs, and Videos. | Serve | 8 |
| Engineering Manager, AI Developer Technology Engineering Manager for NVIDIA's AI Developer Technology team, focused on leading a team to optimize and develop algorithms for Deep Learning and Machine Learning applications, influencing next-generation hardware/software, and collaborating with customers and internal teams. The role involves optimizing training and inference performance on NVIDIA hardware. | ServePost-train | 8 |
| Senior Developer Technology Engineer - AI Senior Developer Technology Engineer focused on researching and optimizing AI/ML workloads for GPU acceleration, involving deep analysis, performance tuning, and collaboration with the developer community and internal teams to influence next-generation hardware and software design. | Serve | 8 |
| Senior HPC Performance Engineer - AI for Science at Scale Senior HPC Performance Engineer focused on optimizing large-scale, CUDA-backed ML training frameworks for AI in Science applications, particularly in digital biology and chemistry. The role involves kernel design, GPU porting, distributed learning, and algorithmic improvements within HPC software stacks. | ServePost-train | 8 |
| Manager, Deep Learning Algorithms Manager for Deep Learning Algorithms at NVIDIA, focusing on productizing DL models, optimizing inference, and leading engineering teams. The role involves working with LLMs/VLMs, inference optimization, and collaborating across NVIDIA to develop state-of-the-art algorithms for GPU-accelerated platforms. | Serve | 8 |
| Distinguished Engineer - Dynamo Distinguished Engineer role focused on NVIDIA Dynamo, an AI inferencing platform. The role involves technical leadership, driving product direction, and contributing to open-source projects to achieve state-of-the-art performance and scalability for AI inference across modalities on NVIDIA hardware. | Serve | 8 |
| Principal Software Engineer – Large-Scale LLM Memory and Storage Systems NVIDIA is seeking a Principal Systems Engineer to design and evolve a unified memory layer for large-scale LLM inference, focusing on KV-cache offload, reuse, and sharing across heterogeneous clusters. The role involves deep integration with LLM serving engines and optimizing performance across GPU, CPU, and storage tiers. | Serve | 8 |
| Senior Software Engineer, Deep Learning - MLIR TRT Senior Software Engineer focused on developing and productizing deep learning solutions for autonomous driving vehicles, specifically involving compiler technology to optimize deep learning inference on NVIDIA hardware. The role requires expertise in deep learning frameworks, compiler technologies, and GPU programming. | Serve | 8 |
| Manager, Deep Learning Algorithms Manager for Deep Learning Algorithms at NVIDIA, focusing on leading engineering efforts for productizing DL models, optimizing inference, and collaborating with research teams to implement and improve algorithms. The role involves managing a team, aligning priorities, and developing the GPU-accelerated DL platform. | Serve | 8 |
| Senior Deep Learning Performance Architect NVIDIA is seeking a Senior Deep Learning Performance Architect to analyze and develop next-generation architectures for AI and high-performance computing. Responsibilities include developing HW architectures for performance and energy efficiency, benchmarking AI workloads, creating simulation tools, and evaluating hardware features. Requires MS/PhD or equivalent experience with 4+ years in parallel computing architectures, GPU/ASIC architecture evaluation for training/inference, and strong Python/C++ skills. | Serve | 8 |
| Senior Manager, Engineering - AI Developer Tools Senior Engineering Manager to lead a team building and evolving AI developer tools and technology for local and cloud GPUs, focusing on the developer experience for AI workflows and managing AI workloads on accelerated infrastructure. | ServeAgent | 7 |
| Senior DL Compiler Engineer -CUDA Tile NVIDIA is hiring a Senior DL Compiler Engineer for the CUDA Tile team. This role involves designing and implementing compiler transformations, developing MLIR-based dialects and lowering passes, and optimizing performance for tile-based kernels on NVIDIA GPUs. The CUDA Tile programming model is a new addition to CUDA, shipped with CUDA 13.1. | Serve | 7 |
| Senior Software Engineer - Storage Software Engineer role focused on designing, building, and operating exascale infrastructure for AI research and development at NVIDIA. The role involves managing distributed systems, large-scale storage, compute orchestration, and automation to support AI workloads across thousands of GPUs and petabytes of storage. | Serve | 7 |
| Principal Developer, AI Networking This role focuses on optimizing AI workloads, specifically LLM training and inference, on large-scale GPU and CPU clusters. The core responsibility is to profile, analyze, and optimize the performance of distributed systems with a strong emphasis on high-performance networking and communication libraries. The engineer will develop tools for performance analysis and collaborate across hardware and software teams to identify and resolve bottlenecks. | ServePretrain | 7 |
| Software R&D Engineer, RTL Optimization Tools Software R&D Engineer at NVIDIA focused on developing internal EDA tools for RTL optimization. The role involves fusing parallel computing, machine learning, and novel algorithms to improve hardware design productivity. It explores the use of LLMs, GNNs, GANs, and Reinforcement Learning for optimization tasks, and requires strong C++ development skills with a focus on graph-based algorithms and optimization. | Serve | 7 |
| Senior Systems Software Engineer, Kubernetes Scale - DGX Cloud Senior Systems Software Engineer focused on scaling NVIDIA DGX Cloud's AI infrastructure, specifically optimizing Kubernetes and distributed inference serving for performance, cost, and reliability. The role involves end-to-end performance characterization, developing automated tests for AI workloads, debugging complex distributed systems, and contributing to open-source communities. | ServeAgent | 7 |
| GPU Architect - New College Grad 2026 NVIDIA is seeking new college graduates for its GPU Architecture Group to design and validate GPU profiling and performance telemetry features. The role involves hardware modeling, test development, and infrastructure, with a focus on the world's leading AI platform. Responsibilities include building and maintaining hardware models, writing and executing test plans, contributing to development infrastructure, and collaborating with cross-functional teams. | Serve | 7 |
| Senior ML Platform Engineer Senior ML Platform Engineer at NVIDIA responsible for architecting, building, and scaling high-performance ML infrastructure using Infrastructure-as-Code (IaC) practices. The role focuses on creating reliable, automated platforms for training and deploying advanced ML models on GPU systems, applying SRE principles, and developing internal automation for ML workflows. Requires strong software engineering skills in Python/Go, experience with Kubernetes/Docker, and a solid understanding of ML workflows. | Serve | 7 |
| Senior Software Engineer - Developer Tools for Deep Learning Senior Software Engineer to enhance NVIDIA's developer tools for deep learning, focusing on neural network design and performance efficiency. The role involves partnering with management and architects, staying updated on research, and working with SOTA computer vision and LLMs. | ServePost-train | 7 |
| Senior Deep Learning Hardware Modeling Architect - LPU NVIDIA is seeking a Senior Deep Learning Hardware Modeling Architect to optimize AI inference speed and efficiency. The role involves driving architectural specifications, developing written specifications for component-level and system-level designs, and embodying these specifications in an executable model. The candidate will ensure high performance using C++ software practices, solid algorithms, and parallelism, and resolve performance and correctness issues across chip and hardware subsystems. | Serve | 7 |
| Senior AI Infrastructure Engineer - DGX Cloud Senior AI Infrastructure Engineer responsible for designing, building, and maintaining large-scale production systems for NVIDIA's DGX Cloud, focusing on AI training and inferencing platforms. This role involves infrastructure automation, distributed systems, performance characterization, and ensuring reliability and availability of GPU cloud services. | Serve | 7 |
| Senior Compiler Engineer - DL NVIDIA is seeking a Senior Compiler Engineer for its Deep Learning Compiler (DLC) team. This role involves analyzing deep learning networks, developing compiler optimization algorithms, and collaborating with framework and hardware teams to accelerate deep learning inference performance. The compiler is critical for data centers, personal devices, automotive, and robotics, aiming for leading inference performance, fast build times, and reduced memory footprints. | Serve | 7 |
| Senior Software Engineer, CUTLASS Kernels Senior Software Engineer to develop and optimize high-performance deep learning kernels (e.g., GEMM, attention, convolution) using CUTLASS CUDA C++ and Python DSL for NVIDIA GPUs and future architectures. The role involves optimizing kernels for peak throughput, collaborating with various NVIDIA teams (architecture, compiler, libraries, DL frameworks), and requires strong C++ and CUDA experience, understanding of computer architecture, and experience with parallel programming languages targeting accelerators. | Serve | 7 |
| Senior Software Engineer, CUTLASS Performance Senior Software Engineer role focused on optimizing the performance of CUTLASS, a high-performance linear algebra and Tensor Core primitive ecosystem for NVIDIA GPUs. The role involves benchmarking deep learning models, identifying performance gaps, developing tooling for optimization, and acting as a performance representative across NVIDIA teams. | Serve | 7 |
| Principal Architect, System Software - Orbital Data Center NVIDIA is seeking a Principal Architect to lead the system software architecture for their Orbital Data Center (ODC) modules, specifically Space-1. This role involves designing and implementing a resilient, production-ready inference platform for the harsh environment of low-Earth orbit, covering the full stack from firmware to AI workloads. The architect will collaborate with hardware teams, drive customer use cases, and ensure the platform operates reliably for 5-year missions, enabling AI adoption in space. | Serve | 7 |
| Software Engineer, TensorRT Specialized Platforms - New College Grad 2025 Software Engineer role focused on developing and optimizing high-performance deep learning inference software (TensorRT) for specialized platforms. Requires strong C++ skills, familiarity with deep learning frameworks, and interest in performance optimization and systems programming. | Serve | 7 |
| Senior Power Analysis and Optimization Engineer This role focuses on applying AI, ML, and LLMs to optimize power efficiency in NVIDIA's GPUs and SoCs. The engineer will develop and productionize ML/RL-based models for power analysis and optimization, design and train custom LLMs for interpreting power data and recommending improvements, and apply AI to tune power-efficient configurations. The role involves analyzing power data, partnering with cross-functional teams, and automating flows. | ServeData | 7 |
| Senior Software Engineer — cuEquivariance Senior Software Engineer to join the cuEquivariance team, which builds and ships production GPU kernels and software interfaces for equivariant deep learning. The role involves CUDA kernel engineering, Python library development (PyTorch/JAX), and collaboration with research teams and external framework developers to accelerate geometric neural networks on NVIDIA GPUs. | Serve | 7 |
| Senior Software Engineer, AI Resiliency Senior Software Engineer to lead the development of AI software resiliency for large-scale AI supercomputers (100,000+ GPUs), focusing on features like fast checkpoint-recovery, error detection/isolation, and straggler/hang detection to minimize cluster downtime. The role involves hands-on C++ and Python coding, debugging, fault tolerance, and collaboration with AI researchers and hardware/software teams, integrating resiliency into AI frameworks like PyTorch and JAX/XLA. Experience with distributed systems, fault tolerance, AI frameworks, and debugging tools is required, with a preference for experience in training models, CUDA/NCCL/MPI, checkpointing strategies, and large-scale AI clusters/HPC. | Serve | 7 |
| Systems Software Engineer - New College Grad 2026 Systems Software Engineer role focused on applying AI and computational methods to accelerate semiconductor manufacturing and design using GPUs. The role involves developing and optimizing complex software solutions, with a strong emphasis on performance and parallel programming. | Serve | 7 |
| Senior Deep Learning Systems Engineer, Datacenters Senior Deep Learning Systems Engineer focused on analyzing and optimizing the performance and power consumption of deep learning applications on datacenter hardware, influencing the design of future AI systems and software stacks. This role involves developing software infrastructure, analysis tools, and profiling methodologies for DL workloads, with a strong emphasis on system architecture and performance analysis. | Serve | 7 |
| Senior System Software Engineer - AI Performance and Efficiency Tools Develops internal profiling, analysis, debugging, benchmarking, and simulation tools for AI workloads running on GPU clusters, supporting AI researchers and SW/HW teams to improve performance and efficiency. | ServeData | 7 |
| Senior Developer Technology Engineer - Windows AI Platform Senior Developer Technology Engineer focused on optimizing and deploying AI/GenAI applications on NVIDIA RTX platforms, particularly LLMs on Windows. This role involves working with internal teams and external developers, analyzing performance, conducting training, and improving user experience with OSS software like Llama.cpp and Ollama. Collaboration with driver and architecture teams is key to influencing future GPU features. | ServeAgent | 7 |
| Senior Deep Learning Tools Engineer – CUDA Tile Senior Deep Learning Tools Engineer at NVIDIA focused on performance validation, analysis, and tracking for AI workloads accelerated by CUDA Tile compiler technologies and GPU systems. The role involves designing and developing performance testing frameworks, building automated CI/CD pipelines, implementing benchmarking systems, analyzing performance trends, and collaborating with compiler and architecture teams to resolve performance issues. Requires strong programming skills in Python, experience with CI/CD, deep learning frameworks, and hardware-aware performance analysis. | Serve | 7 |
| Senior Systems Software Engineer - GPU Performance at Scale Senior Systems Software Engineer focused on GPU performance at scale for AI workloads, involving collaboration with various hardware and software teams to optimize large-scale computing platforms and deliver insights into AI workload performance. | Serve | 7 |
| Senior Compiler Engineer - AI NVIDIA is seeking a Senior Compiler Engineer with expertise in machine learning and compiler technologies to focus on applied AI and ML within compilers and development tools. The role involves working with Python, C/C++, Julia, and Lisp/Scheme, with a strong foundation in compilers, code generation, and GPU architecture. Experience with LLVM is a plus. | Serve | 7 |
| Distinguished Software Architect - Deep Learning and HPC Communications Distinguished Software Architect role focused on designing and researching next-generation communication libraries and platforms for Deep Learning and High Performance Computing at NVIDIA. The role involves co-designing HW/SW solutions with GPU, Networking, and SW architects, driving adoption of new communication technologies, and keeping up with DL research. Requires deep expertise in HPC, parallel programming, communication runtimes, system/GPU architecture, and networking, with strong programming skills in C/C++. | Serve | 7 |
| Manager, Next-Gen AI Cluster Validation Manager to lead a team developing and validating next-generation NVIDIA AI supercomputing systems, integrating new compute, networking, storage, and software. Focus on building a platform for software development, automation, and performance engineering, and supporting large-scale deployments for AI and HPC. | Serve | 7 |
| GPU Power Architect - New College Grad 2026 NVIDIA is seeking a New College Grad Datacenter GPU Power Architect to contribute to the research and development of energy-efficient GPU and SOC architectures. The role involves developing power estimation models and tools, exploring energy efficiency at GPU and Datacenter levels, and deploying machine learning techniques to model GPU, CPU, Switch, and platform performance and power. The candidate will understand GenAI/HPC workload characteristics to drive HW/SW features for Perf@Watt improvements. | Serve | 7 |