1 day ago
Base Salary
$152k - $242k/yr
Responsibilities
- Build and deliver agentic AI systems that automate silicon bring-up, testing, validation, debugging, and engineering workflows.
- Build scalable AI infrastructure, services, APIs, and reusable platforms for AI-powered applications.
- Integrate AI agents with engineering tools, knowledge bases, data platforms, and existing business processes.
- Partner with cross-functional teams to identify use cases, define requirements, prototype solutions, and deploy production systems.
- Establish evaluation, observability, security, and reliability practices for AI systems.
- Drive projects from concept through adoption, measure outcomes, and continuously improve efficiency.
Requirements
- Bachelor’s or master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.
- At least 5 years of experience delivering production software, infrastructure, platform, or AI solutions.
- Strong programming skills in Python and C/C++.
- Experience building applications with large language models, AI agents, retrieval-augmented generation, tool use, or workflow orchestration.
- Ability to build scalable services, APIs, data pipelines, and production software infrastructure.
- Strong problem-solving, debugging, and system-design skills with a history of shipping reliable systems.
- Effective collaboration and communication skills across technical and business teams.
- Preferred qualifications include GPU computing, CUDA, GPU architecture, silicon bring-up, engineering diagnostics, hardware development workflows, MLOps, model evaluation, AI observability, open-source AI/ML, developer tools, or internal developer platforms experience.
Benefits
- Eligible for equity and benefits.
- Base salary varies by location, experience, and comparable employee pay; the stated base salary range is USD 152,000–241,500.
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.