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 |
|---|---|---|
| Solutions Architect – AI Factory Solutions Architect role focused on designing, building, and operationalizing large-scale AI factories and GenAI/Agentic AI solutions for enterprise customers, leveraging NVIDIA's technology stack. This involves hands-on work with compute, networking, software, and cluster management tools. | Agent | 8 |
| Senior Libraries Engineer – AI and HPC Senior Libraries Engineer at NVIDIA focused on building and optimizing GPU/CPU accelerated data processing software libraries for AI, data analytics, computer vision, and scientific simulations. The role involves developing scalable library software, performance tuning, optimization, and providing technical leadership. | Serve | 7 |
| Dataflow Development Engineer - LPU Hardware DataFlow Develop, build, and improve dataflow systems at the hardware–software boundary for FPGA accelerators, focusing on implementing and tuning dataflow pipelines, creating host-side drivers and runtimes, and jointly inventing hardware and software for deterministic, low-latency execution. This role directly affects latency, efficiency, and resource usage for inference at scale. | — | 5 |
| Senior Software Developer, AI Networking Senior Software Developer role focused on developing a high-performance, low-level infrastructure for AI networking acceleration, specifically for inference. The role involves working with hardware offloads, GPU kernels, and RDMA, aiming to optimize the inference process on large-scale supercomputers and data centers. | Serve | 5 |
| Formal Verification Engineer - New College Graduate NVIDIA is seeking a Formal Verification Engineer to verify the design and implementation of GPUs. This role involves using formal verification algorithms to prove the correctness of logic problems, identifying key behaviors for verification, implementing testplans using formal techniques, driving tool performance, developing automation scripts, and collaborating with other teams to ensure bug-free silicon products. The position requires a BS/MS/Ph.D. in a relevant field, strong analytical and coding skills (C, Perl, Python), and debugging abilities. Preferred qualifications include knowledge of formal verification methodologies and experience with Verilog/System Verilog, SVA assertions, and RTL code. | — | 0 |