NVIDIA
- HQ
- California, US
- Founded
- 1993
- Size
- 35,000+
- Website
- nvidia.com
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 |
|---|---|---|
| High-Performance LLM Training Engineer - New College Grad 2026 NVIDIA is seeking an experienced engineer to optimize LLM training workloads on high-performance computing systems, focusing on software stack optimization for thousands of GPUs and influencing future hardware roadmaps. The role involves performance analysis, profiling, and implementation across the deep learning platform, from drivers to frameworks, and contributing to MLPerf benchmarks. | Data | 9 |
| Senior Systems Software Engineer, AI Stack and Performance - DGX Station Senior Systems Software Engineer focused on optimizing AI stack performance and readiness on NVIDIA's DGX Station, a workstation-class AI computer. The role involves profiling, identifying bottlenecks, and driving optimizations across the full stack from GPU kernels to applications, ensuring AI workloads like LLM inference and agents run efficiently in multi-GPU, multi-user configurations. Collaboration with framework, compiler, and GPU architecture teams is critical. |
| ServeShip |
| 9 |
| Senior Machine Learning Engineer, Perception - Autonomous Driving NVIDIA is seeking a Senior Machine Learning Engineer for their Autonomous Driving Perception team. The role involves designing and developing end-to-end deep learning solutions for perception modules, focusing on road layout detection, lane structures, and other critical driving components. The engineer will also drive data-driven development, leverage simulation and augmentation, and productize solutions meeting safety and latency requirements. Experience with deep learning frameworks, Python/C++, and perception for autonomous driving or robotics is essential. | ShipData | 9 |
| Senior Software Engineer, DGX Cloud AI Infrastructure Senior Software Engineer to lead the bring-up, triage, benchmarking, analysis, and optimization of distributed training and inference workloads across NVIDIA GPU platforms at scale. This role involves setting technical direction for communication libraries, model frameworks, and inference/training stacks, leading performance and reliability investigations, defining benchmarking and qualification processes, and building resilience capabilities for large clusters. | ServePost-train | 9 |
| Senior Deep Learning Performance Architect NVIDIA is seeking a Senior Deep Learning Performance Architect to analyze and develop next-generation architectures for AI and HPC applications. The role involves developing innovative architectures, analyzing performance/cost/power trade-offs using models and simulators, understanding hardware/software interplay, and evaluating PPA for architectural decisions. Collaboration with software, product, and research teams is key. Requires MS/PhD, 6+ years experience, strong background in GPU/Deep Learning ASIC architecture for distributed training/inference, performance modeling, and ML/DL fundamentals, particularly transformer architectures. Proficiency in Python, C, C++ is essential. | Serve | 9 |
| AI Inference Performance Engineer - New College Grad 2026 NVIDIA is seeking an AI Inference Performance Engineer to optimize and benchmark GenAI inference on their accelerators, working with frameworks like TensorRT-LLM, SGLang, and vLLM. The role involves driving industry benchmark results, defining cutting-edge workloads, architecting distributed inference, establishing performance methodology, and influencing the ecosystem through open-source contributions and cross-functional partnerships. Requires strong programming skills, DL framework expertise, and a deep understanding of LLM inference mechanics. | Serve | 9 |
| Senior Software Engineer, Generative AI Research NVIDIA is seeking a Senior Software Engineer for Generative AI Research to build and operate scalable infrastructure for training their world foundation model for physical AI, Cosmos. This role involves designing and developing high-throughput systems for data processing, retrieval, and workflow orchestration, improving system reliability and performance, and contributing to long-term infrastructure strategy for training, data management, and large-scale compute efficiency. The role requires a strong engineering background in distributed systems, ML infrastructure, or large-scale compute/data platforms, proficiency in Python and C++/Go/Rust, and experience with orchestration systems and data pipelines. Experience with large-scale model training infrastructure, distributed compute, synthetic data, or multimodal datasets is a plus. | DataPretrain | 9 |
| Senior Software Manager, Agentic AI Senior Software Manager to lead a team building agentic AI solutions for chip design workflows, involving coding agents, custom skills, and integration with enterprise systems. The role requires technical leadership in designing, developing, and deploying AI applications using LLMs and agentic systems, including model customization (fine-tuning, RL, instruction tuning) and overseeing retrieval/generation algorithms for enterprise data. Collaboration with cross-functional teams and ensuring high technical standards for evaluation, guardrails, and monitoring are key. | AgentPost-train | 9 |
| Senior Software Engineer - Agentic AI Senior Software Engineer role focused on leading Agentic AI solutions, including sophisticated AI agents and fine-tuning, integrating them with enterprise production systems. The role involves designing, developing, and deploying AI applications using LLMs, Agentic frameworks, and optimizing retrieval/generation algorithms for enterprise data (text, code, images) to build advanced AI applications for engineering assistants and multi-turn, multi-modal dialogue systems, ultimately solving complex problems in chip design. | AgentPost-train | 9 |
| Senior Performance Architect, Nemotron NVIDIA is seeking a Senior Performance Architect for Nemotron to focus on deep model-system-hardware co-design. The role involves developing high-fidelity performance models to evaluate architectural choices, predict deployment efficiency, and ensure Pareto-optimal trade-offs for future Nemotron models. This position will guide future software and hardware roadmaps by modeling end-to-end performance impact of GenAI workflows and collaborating with research, framework, compiler, and hardware teams. | Serve | 9 |
| Senior Machine Learning Engineer - Physical AI and Synthetic Data Generation NVIDIA is seeking a Senior Machine Learning Engineer to join their Physical AI team. The role focuses on architecting and developing generative pipelines for high-fidelity synthetic data using multimodal and diffusion models. Responsibilities include building and fine-tuning large-scale models, applying user controls for data synthesis, establishing quality assurance pipelines, and leading the generation of massive training datasets. The role requires deep technical knowledge in image/video synthesis, strong programming skills, and experience in assessing synthetic data impact on model performance. | DataPost-train | 9 |
| Senior DL Algorithms Engineer - Inference Performance Senior engineer to optimize LLM/Omni model inference performance on NVIDIA's accelerated inference software stack, working across hardware and software layers. Involves enabling and optimizing open models, contributing code to frameworks like TRT-LLM and vLLM, profiling bottlenecks, and benchmarking. | Serve | 9 |
| Senior Research Engineer - AI Coding Tools Senior Research Engineer at NVIDIA focused on building and improving AI coding agents, fine-tuning code LLMs, designing evaluations, and developing interfaces for AI agents to interact with NVIDIA's developer tools. The role involves shipping novel agents and features, contributing to benchmarks, and generating synthetic data for AI-for-code applications. | AgentPost-train | 9 |
| Principal High-Performance LLM Training Engineer NVIDIA is seeking a Principal Engineer to lead performance analysis and optimization of large-scale AI training and post-training workloads on NVIDIA's hardware and software stack. The role involves deep technical analysis across compute, memory, communication, and frameworks to improve efficiency and influence future roadmaps. | PretrainPost-train | 9 |
| Senior Software Engineer, AI Inference Systems Senior Software Engineer focused on building and optimizing AI inference systems, including vLLM, GPU kernels, and orchestration for large-scale model deployments. The role involves performance engineering, benchmarking (MLPerf), and potentially research integration. | Serve | 9 |
| Senior Deep Learning Software Engineer Senior Deep Learning Software Engineer to design and build an automated inference and deployment solution with a scalable architecture focusing on ease-of-use and compute efficiency. The role involves developing features in high-level frameworks, implementing a high-performance execution environment, and low-level GPU optimizations. | Serve | 9 |
| Senior Software Engineer, RL Post-Training Frameworks NVIDIA is seeking a Senior Software Engineer to build and scale RL post-training infrastructure, focusing on distributed systems, high-performance computing, and deep learning infrastructure. The role involves architecting and optimizing RL training-inference-rollout loops, ensuring fault tolerance and elastic scaling, and collaborating with researchers and hardware teams. | Post-trainServe | 9 |
| Manager, Deep Learning – Autonomous Vehicles and Robotics Manager for a Deep Learning Engineering team focused on delivering production-quality deep learning solutions for autonomous vehicles and robotics on edge hardware. The role involves leading a team, defining technical initiatives, and collaborating with automotive OEMs and robotics partners to optimize solutions on NVIDIA platforms, working at the intersection of model architectures, compiler technology, and embedded deployment. | ServePost-train | 9 |
| Senior AI Software Engineer, Kernel Libraries Senior AI Software Engineer focused on developing kernel libraries and inference systems software to accelerate AI workloads, including LLMs and agents, on NVIDIA's hardware. Responsibilities include innovating and optimizing kernels, designing abstractions for serving engines, and building compilers/runtimes. | Serve | 9 |
| Senior Software Engineer, AI and DL Kernel Libraries Develops libraries, code generators, and GPU kernel technologies for NVIDIA's AI inference systems software stack, focusing on accelerating AI inference through efficient kernels, abstractions, and runtimes for LLMs and agents. | Serve | 9 |
| Senior DL Software Engineer, Model Optimization and Edge Deployment - Autonomous Vehicles Senior DL Software Engineer focused on optimizing and deploying large multimodal models (LLMs/VLMs) for real-time robotic execution in autonomous vehicles. The role involves advanced model compression, quantization, pruning, distillation, and inference optimization techniques for edge deployment on NVIDIA hardware, integrating with C++ production environments. | ServeAgent | 9 |
| Senior Deep Learning Software Engineer, LLM Performance Senior Deep Learning Software Engineer focused on optimizing LLM inference performance on NVIDIA accelerators using frameworks like TensorRT LLM, VLLM, and Triton. The role involves implementing and scaling inference, serving, and deployment algorithms, collaborating with various teams, and contributing to NVIDIA/OSS LLM frameworks. | Serve | 9 |
| Senior Machine Learning and Simulation Engineer - Autonomous Vehicles Senior ML Engineer focused on building and optimizing large-scale Reinforcement Learning (RL) training frameworks for multi-modal Autonomous Vehicle (AV) foundation models. This role involves designing simulation and data processing pipelines, refining reward functions, and ensuring the reliability of training workflows on GPU clusters, with a focus on closed-loop simulation for training end-to-end AV models. | Post-trainAgent | 9 |
| Senior Software Engineer - AI Inference Senior Software Engineer focused on optimizing and contributing to open-source LLM inference serving engines like vLLM and SGLang to run efficiently on NVIDIA GPUs, focusing on high-throughput, low-latency inference at scale. | Serve | 9 |
| Principal Engineer - AI Agents and Systems Principal Engineer to lead the deployment of advanced AI agent frameworks and local runtimes on Windows and NVIDIA GPUs, focusing on open-source agents, local inference, privacy, and security for consumer PCs. | AgentServe | 9 |
| Senior Software Engineer - Agentic Memory Senior Software Engineer role focused on developing and researching agentic memory systems, including designing benchmarks, generating synthetic data, running experiments, and contributing to open-source evaluation tools. The role involves partnering with other NVIDIA teams deploying agents and advancing the state of the art in agentic memory evaluation. | AgentEval Gate | 9 |
| Senior High-Performance LLM Training Engineer NVIDIA is seeking an experienced Senior High-Performance LLM Training Engineer to optimize LLM training workloads on advanced computing systems. The role focuses on improving the efficiency of NVIDIA's high-performance LLM software stack using frameworks like PyTorch and JAX for training on thousands of GPUs, and influencing future hardware roadmaps. | Data | 9 |
| Senior Manager, Software Engineering - JAX Senior Engineering Manager to define and drive NVIDIA's JAX strategy, coordinating multiple teams to ensure JAX delivers peak performance across heterogeneous hardware (GPUs, CPUs, LPUs). The role involves supporting emerging needs across training, post-training, inference, and robotics, bridging new hardware capabilities with AI trends. Key responsibilities include driving engineering contribution strategy, promoting teamwork, building partnerships with open-source projects, designing processes, and leading a high-performing engineering organization. | ServePost-train | 9 |
| Deep Learning Software Engineer, TensorRT Performance - New College Grad 2026 NVIDIA is seeking a Deep Learning Software Engineer to analyze and improve the performance of their inference ecosystem, focusing on TensorRT and related frameworks. The role involves optimizing inference solutions for various NVIDIA accelerators, developing new model pipelines, and collaborating with cross-functional teams on generative AI, robotics, and vision/speech understanding applications. | Serve | 9 |
| Deep Learning Senior Engineer, End-To-End Autonomous Driving NVIDIA is looking for a Deep Learning Senior Engineer to design, implement, and deploy end-to-end autonomous driving systems. The role focuses on leveraging LLMs, VLMs, and VLAs for reasoning and planning, involving model training, pre-training, fine-tuning, and integration into safety-critical vehicle firmware. Experience with production-grade ML models and C++ for deployment is required. | Post-trainAgent | 9 |
| Manager, Large Language Model Inference Manager for Large Language Model Inference at NVIDIA, focusing on developing and optimizing LLM/VLM/VLA inference software for NVIDIA GPUs and hardware platforms. The role involves leading a team in specialized kernel development, runtime optimizations, and frameworks for LLM inference, with a strong emphasis on delivering production-grade, high-performance software. | Serve | 9 |
| Senior Deep Learning Software Engineer, TensorRT Performance NVIDIA is seeking a Senior Deep Learning Software Engineer to analyze and improve the performance of their deep learning inference ecosystem, specifically focusing on TensorRT. The role involves optimizing inference solutions for various NVIDIA accelerators, contributing to inference frameworks, and developing new model pipelines for generative AI and other applications. | Serve | 9 |
| Senior Perception Engineer, Obstacle Foundation Models - Autonomous Vehicles NVIDIA is seeking a Senior Perception Engineer to design and productize its next-generation autonomous driving perception stack. The role focuses on the core 3D obstacle perception pipeline, involving architecture and algorithm design, and hands-on implementation using transformer-based, multi-modal, and vision-language techniques. Responsibilities include developing perception models, building production-grade deep learning models with pretraining and fine-tuning, defining KPI frameworks, contributing to data strategy, and collaborating with safety and systems teams. Requires a PhD/MS/BS with significant relevant experience, proficiency in PyTorch, Python/C++, and experience in data-driven development. Experience with autonomous driving/robotics perception, embedded platforms, optimization, and publications in leading conferences are desirable. | ShipPost-train | 9 |
| Principal Deep Learning Senior Engineer, End-To-End Autonomous Driving NVIDIA is seeking a Principal Deep Learning Senior Engineer to design, implement, and deploy end-to-end autonomous driving systems. The role focuses on leveraging LLMs, VLMs, and VLAs for advanced reasoning and planning in vehicles and robotics, involving model training, pre-training, fine-tuning, and integration into safety-critical systems. | Post-trainAgent | 9 |
| Principal Deep Learning Engineer – Perception, Autonomous Driving Principal Deep Learning Engineer for NVIDIA's Autonomous Driving Perception team, focusing on developing, training, and deploying state-of-the-art perception systems (detection, segmentation, tracking) for vehicles. The role involves leading the end-to-end productization of these models, ensuring high quality and safety, defining data strategy, and providing technical leadership. Requires extensive experience in deep learning for computer vision and shipping commercial DL products. | ShipServe | 9 |
| Principal Perception Engineer, Obstacle Foundation Models - Autonomous Vehicles Principal Perception Engineer at NVIDIA for Autonomous Vehicles, focusing on designing and productizing next-generation 3D obstacle perception stacks using deep learning, transformers, and multi-modal techniques. The role involves technical leadership, hands-on algorithm development, production-grade model development, data strategy, and collaboration with safety and systems teams for large-scale deployment. | AgentData | 9 |
| Senior Deep Learning Communication Architect Senior Deep Learning Communication Architect role focused on optimizing communication performance for large-scale distributed deep learning training and inference. This involves identifying bottlenecks, designing efficient protocols, collaborating on hardware/software co-design, and exploring new communication technologies. The role requires deep understanding of parallelism techniques and experience with DNN frameworks and GPU computing. | ServePost-train | 9 |
| Senior Deep Learning Performance Architect - LPU NVIDIA is seeking a Senior Deep Learning Performance Architect to focus on hardware-software co-design for AI Inference performance. The role involves designing GPU and system architectures, analyzing deep learning algorithms, building performance models, and collaborating with various teams to guide AI direction. | Serve | 9 |
| Senior Systems Software Engineer - Deep Learning Solutions Senior Systems Software Engineer focused on optimizing deep learning inference for autonomous vehicles and robotics on edge devices. Requires deep understanding of model architectures, kernel trace analysis, and evaluation of modern architectures on GPUs/SOCs, with a focus on TensorRT and compiler technology for embedded hardware. | ServePost-train | 9 |
| AI Inference Performance Engineer This role focuses on optimizing and benchmarking Generative AI inference performance on NVIDIA's hardware accelerators, specifically working with frameworks like TensorRT-LLM, SGLang, and vLLM. The engineer will drive industry benchmark results by implementing optimizations in quantization, scheduling, memory management, and distributed inference. They will also define and optimize cutting-edge workloads, architect distributed inference systems from single-GPU to rack-scale, establish performance methodology using profiling, and contribute to open-source projects. The role requires strong programming skills (Python/C++), expertise in DL frameworks, and a deep understanding of LLM/VLM architectures and inference mechanics. | Serve | 9 |
| Senior Deep Learning Engineer - Model Evaluation & AI Systems Senior/Principal Deep Learning Engineer focused on building evaluation methodologies and infrastructure for AI models (LLMs, RAG, agents, vision/multimodal), including contributing to an open-source platform and collaborating with the community. The role involves working with model training, inference, and product teams to provide evaluation signals for release and optimization decisions. | Eval GateAgent | 9 |
| Senior Deep Learning Engineer Senior Deep Learning Engineer at NVIDIA focused on optimizing inference for next-generation AI workloads including multi-agent systems and generative multimodal models. The role involves characterizing emerging workloads and developing novel optimization methods across the inference stack, from algorithmic to system level, on NVIDIA hardware. Collaboration with research, framework development, and silicon architecture teams is key. | ServeAgent | 9 |
| Lead Principal Engineer, Enterprise Agentic AI Platform Lead Principal Engineer for Enterprise Agentic AI Platform at NVIDIA, focusing on building and scaling production-grade agentic AI systems, including multi-agent orchestration, memory systems, and evaluation pipelines. Requires deep expertise in distributed systems, Kubernetes, GPU inference, and hands-on coding in Python/Go. | AgentServe | 9 |
| Senior Deep Learning Compiler Engineer - XLA Senior Deep Learning Compiler Engineer focused on optimizing inference and training performance for JAX and OpenXLA on NVIDIA GPUs. Develops compiler optimization algorithms, graph partitioning, tensor sharding, and code generation using MLIR, LLVM, and Triton. | ServePost-train | 9 |
| Principal Software Engineer - AI Inference Principal Software Engineer focused on advancing open-source LLM serving, specifically contributing to inference engines like vLLM and SGLang, optimizing them for NVIDIA GPUs and systems to achieve high-throughput, low-latency inference at scale. The role requires deep technical expertise in inference runtime architecture, GPU performance engineering, and distributed systems. | Serve | 9 |
| Senior DL Algorithms Engineer - Inference Performance Senior DL Algorithms Engineer focused on optimizing inference performance for language and multimodal models using NVIDIA's inference stack (NIMs, TRT-LLM). Role involves profiling, analysis, and collaboration across hardware/software layers to maximize performance on GPUs. | Serve | 9 |
| Senior DGX Cloud AI Infrastructure Software Engineer NVIDIA is seeking a Senior DGX Cloud AI Infrastructure Software Engineer to develop and optimize infrastructure software and tools for large-scale AI training, post-training, and inference. The role focuses on improving efficiency and resiliency of AI workloads, co-designing APIs, and enhancing AI platforms, requiring strong debugging and distributed systems experience. | ServePost-train | 9 |
| Agent RL Infra Engineer NVIDIA is seeking an engineer to develop and productionize reinforcement learning (RL) capabilities for agent teams within an enterprise context. The role involves evaluating and adapting RL approaches, designing reward environments, operationalizing training backends, and integrating with existing ML services. Responsibilities include leading data curation, designing RL training loops, integrating with GPU infrastructure, building observability, and collaborating with various platform and customer teams. The ideal candidate has extensive experience in operationalizing fine-tuning and RL techniques, familiarity with distributed training frameworks and MLOps, and proficiency in relevant programming languages. | Post-trainAgent | 9 |
| Director of Engineering, End to End Autonomous Driving NVIDIA is seeking a Director of Engineering to lead the design and deployment of end-to-end autonomous driving systems. This role focuses on leveraging LLMs, VLMs, and VLAs for advanced planning and reasoning in vehicles and robotics, involving strategic leadership, team management, and technical oversight of ML model development and integration into safety-critical production environments. | ShipPost-train | 9 |
| Director, Perception - Autonomous Vehicles Director of Perception for Autonomous Vehicles at NVIDIA, leading teams to develop and deploy state-of-the-art deep learning models for real-time 3D world reconstruction and navigation. This role involves end-to-end ownership of the ML lifecycle, from data generation to deployment on NVIDIA DRIVE platforms, with a strong emphasis on safety-critical systems and cross-functional collaboration. | ShipData | 9 |