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 Senior Engineer, End-To-End Autonomous Driving NVIDIA is seeking a Deep Learning Senior Engineer to design, implement, and deploy end-to-end autonomous driving systems. The role focuses on AI 2.0, leveraging LLMs, VLMs, and VLAs for reasoning and planning in autonomous vehicles and robotics. Responsibilities include training large-scale models, building and fine-tuning LLM/VLM/VLA systems, exploring data generation strategies, and deploying models in production environments, integrating them with vehicle firmware. | Post-trainAgent | 9 |
| Solutions Architect, GenAI NVIDIA is seeking a Solutions Architect with deep expertise in Generative AI (LLM) model building, focusing on training LLMs at scale and customizing them. This role involves designing solutions, leading workshops, and collaborating with internal teams to build full-stack GenAI solutions for enterprise use cases. The position requires significant experience in deep learning and generative AI, with an emphasis on large-scale LLM training. |
| Post-trainServe |
| 9 |
| Senior Solutions Architect - Generative AI Senior Solutions Architect specializing in Generative AI, focusing on training LLMs, fine-tuning, and RAG implementation. The role involves architecting end-to-end solutions, collaborating with customers and sales teams, and providing technical leadership for LLM training and Agentic AI workflows on NVIDIA platforms. | Post-trainAgent | 9 |
| LLM Reinforcement Learning Framework Engineer NVIDIA is seeking an LLM Reinforcement Learning Framework Engineer to develop and deploy RL algorithms for LLM post-training, focusing on improving reasoning and alignment. The role involves integrating RL components into NVIDIA's LLM stack, crafting experiments, and ensuring production readiness. Requires strong Python, PyTorch, and practical RL experience with LLMs, along with familiarity in async/distributed orchestration. | Post-trainAgent | 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 |
| 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 |
| Deep Learning Solution Architect NVIDIA is seeking a Deep Learning Solution Architect to drive the research, development, and optimization of Reinforcement Learning algorithms and infrastructure for LLMs and multimodal models. The role involves collaborating with internal teams, improving customer engagements with NVIDIA RL technologies, and developing toolchains and documentation. Requires MS/PhD, 5+ years of experience in RL, LLM training, or multimodal learning, proficiency in PyTorch, and strong engineering skills in distributed training or orchestration. | Post-trainAgent | 9 |
| Senior Applied Scientist - Sovereign AI Senior Applied Scientist/AI Engineer at NVIDIA focusing on Sovereign AI efforts. The role involves end-to-end model training (pre-training, CPT, SFT, alignment), rigorous evaluation and benchmarking, and inference optimization using tools like TensorRT-LLM and NIM. Requires strong Python, PyTorch, and experience with large-scale ML frameworks. | Post-trainServe | 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 |
| 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 |
| Deep Learning Engineer - LLM and VLM Model Compression NVIDIA is seeking a Deep Learning Engineer with 8+ years of experience to build deep learning frameworks for LLM and VLM model compression. The role involves designing and implementing algorithms for pruning, NAS, and distillation, experimenting with model compression, and collaborating with researchers. Experience with PyTorch, LLM/VLM training or inference, and DL fundamentals are required. Experience with model compression techniques, building DL frameworks, and GPU programming are preferred. The role is based in Poland or Switzerland, with a salary range of 292,500 PLN - 650,000 PLN. | Post-trainServe | 9 |
| Senior Deep Learning Scientist, Multimodal Conversational AI Senior Deep Learning Scientist role focused on developing, training, fine-tuning, and deploying streaming multimodal conversational AI systems. This includes speech, audio, vision, voice chat, and action, as well as human-AI interaction. The role involves applying research to define algorithmic improvements and scale them through the Nemotron platform, working on high-impact LLM products. | Post-trainAgent | 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 |
| Senior Research Engineer Neural Reconstruction Senior Research Engineer focused on neural reconstruction, developing and integrating neural rendering approaches for generative video, segmentation, and 3D reconstruction. The role involves adapting and fine-tuning generative models, collaborating on ML workflows, and contributing to core NVIDIA products. Requires strong Python and ML library skills, with experience in training and optimizing models. | Post-trainServe | 9 |
| Senior Software Engineer – AI and Autonomous Driving Senior Software Engineer to build and deploy production AI for autonomous vehicles, focusing on training, fine-tuning, and optimizing deep learning models for real-time inference on NVIDIA GPUs. Requires strong C++/Python, deep learning training experience, and Linux development skills, with a preference for GPU programming, computer vision, or robotics. | Post-trainServe | 9 |
| AI Research Engineer - Applied Scientist Compilers AI Research Engineer/Applied Scientist focused on Compilers/Low-level optimization to develop AI compiler solutions for NVIDIA's software stack and GPU acceleration. Responsibilities include applying AI to compilation, implementing AI-based solutions for GPU programming, building training pipelines (fine-tuning, RL), defining model I/O, developing evaluation frameworks, prompt engineering, integrating learned policies, prototyping models, creating datasets, and applying RL for optimization. | Post-trainServe | 8 |
| Senior Scientific Machine Learning Engineer – Earth-2 Develops and enhances machine learning frameworks (NVIDIA PhysicsNeMo, NVIDIA Earth2Studio) for scientific ML technology in weather, climate, and earth system modeling. Focuses on implementing new deep learning techniques and enhancing Earth-2 technologies. | Post-train | 8 |
| Senior System Software Engineer, 3D Computer Vision Senior System Software Engineer focused on 3D Computer Vision at NVIDIA, involving the development and deployment of advanced neural reconstruction models for generating 3D scenes. The role requires strong programming skills in Python and C/C++, a background in computer vision and deep learning, and experience with production-grade software development. | Post-trainServe | 8 |
| Solution Architect, Financial Services Solutions Architect for Financial Services at NVIDIA, focusing on guiding customers in leveraging NVIDIA's AI technologies, particularly in areas like model distillation, domain adaptation, reinforcement learning, and post-training algorithms. The role involves technical advocacy, collaborative innovation, and knowledge sharing within the financial services sector, requiring expertise in AI frameworks, Python, distributed computing, and the AI model lifecycle. | Post-trainPretrain | 8 |
| Senior Solutions Architect, AI Factory NVIDIA is seeking a Senior Solutions Architect with expertise in AI Supercomputing to support academic and commercial groups using NVIDIA products for deep learning, data analytics, and scientific simulation. The role involves understanding customer needs, developing solutions, demonstrating workflows, and communicating requirements to NVIDIA Engineering. Requires 3+ years of Deep Learning research experience, experience with LLM training and adaptation, and familiarity with DL frameworks and Generative AI. | Post-train | 8 |
| Senior Application Engineer Senior Application Engineer role focused on accelerating materials and chemical discovery using AI, involving collaboration with developers and researchers on building, fine-tuning, and optimizing AI models and agentic workflows. The role requires experience with AI frameworks, benchmarking domain-specific models, and communicating technical value. | Post-trainAgent | 7 |