1 day ago
Base Salary
$224k - $431k/yr
Responsibilities
- Architect and build scalable, reliable systems for agentic AI across runtimes, harnesses, inference, evaluation, and orchestration.
- Solve large-scale systems challenges involving distributed execution, data and ETL pipelines, HPC, cloud, Kubernetes, and GPU compute environments.
- Optimize systems for reliability, scalability, performance, resource utilization, and developer experience.
- Prototype emerging ideas and write high-quality production software.
- Provide technical leadership across research, engineering, product, and infrastructure teams.
Requirements
- Bachelor’s or master’s degree, or equivalent experience, in Computer Science, Computer Engineering, AI, or a related field.
- 12+ years of relevant industry experience.
- Strong knowledge of modern AI, including LLMs, multimodal models, inference, agentic AI, and evaluation.
- Deep expertise in software architecture, distributed systems, and large-scale systems design.
- Strong hands-on programming skills in Python, C++, Go, Rust, or similar languages.
- Experience building large-scale systems involving distributed execution, data processing and ETL, workflow orchestration, HPC, cloud, or GPU infrastructure.
- Ability to reason across AI model behavior, application logic, runtimes, compute, and infrastructure.
- Track record of taking ambiguous and complex technical problems from architecture through implementation and production.
- Preferred: experience with LLM/VLM inference, model serving, model routing, inference optimization, AI evaluation, benchmarking, experimentation, or large-scale AI infrastructure.
- Preferred: experience building reusable platforms supporting heterogeneous AI workloads and compute environments.
Benefits
- Eligible for equity and benefits.
- Base salary varies by location, experience, and comparable employee pay; the posting lists ranges for Level 5 and Level 6.
- Applications accepted at least until September 13, 2026.
- This posting is for an existing vacancy.
Tech Stack
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.