Senior AI Engineer, High Performance AI

About the role

NVIDIA is building the next era of computing by tapping into the unlimited potential of AI. As an NVIDIAN, you’ll work in a diverse, supportive environment where everyone is inspired to do their best work. We are seeking an outstanding High Performance AI Engineer to build groundbreaking multi-agent systems for the CUDA ecosystem. You will design and develop agentic runtimes and compiler-integrated orchestration that integrate with NVIDIA’s software stack to accelerate modern agent workloads powered by foundational models. Your work will include new agent abstractions, GPU-centric runtimes, and compiler- or runtime-driven system solutions to accelerate agent planning, tool-use, code generation, and other high-impact AI workloads. You will collaborate closely with internal NVIDIA software and hardware teams to push the latest developments into NVIDIA products.

Responsibilities

• Design, build, and optimize agentic AI systems for the CUDA ecosystem.
• Co-design agentic system solutions with software, hardware, and algorithm teams; influence and adopt new capabilities as they become available.
• Develop reproducible, high-fidelity evaluation frameworks covering performance, quality, and developer productivity.
• Collaborate across the AI stack—from hardware through compilers/toolchains, kernels/libraries, frameworks, distributed training, and inference/serving—and with model/agent teams.

Requirements

• Bachelor’s degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); MS or PhD preferred.
• 3 years+ industry or academia experience with AI systems development; exposure to building foundational models, agents, or orchestration frameworks; hands-on experience with deep learning frameworks and modern inference stacks.
• Strong C/C++ and Python programming skills; solid software engineering fundamentals.
• Experience with GPU programming and performance optimization (CUDA or equivalent).

Qualifications

• Strong experience in building/evaluating deep learning models, coding agents, and developer tooling.
• Demonstrated ability to optimize and deploy high-performance models, including on resource-constrained platforms.
• Demonstrated ability in GPU performance optimizations, evidenced by benchmark wins or published results.
• Publications or open-source leadership in deep learning, multi-agent systems, reinforcement learning, or AI systems; contributions to widely used repos or standards.

Pay

Base salary range: $152,000 – $241,500 USD, determined by location, experience, and internal equity. Eligible for equity and benefits.