High Performance AI Engineer

Role: High Performance AI Engineer

Build and optimize agentic (multi-agent) AI systems for the CUDA ecosystem, working on GPU-centric runtimes and compiler-integrated orchestration.

Responsibilities

• Design, build, and optimize agentic AI systems for CUDA.
• Co-design agentic system solutions with software, hardware, and algorithm teams; help influence and adopt new capabilities.
• Develop reproducible, high-fidelity evaluation frameworks for performance, quality, and developer productivity.
• Collaborate across the AI stack, from hardware through compilers/toolchains, kernels/libraries, frameworks, distributed training, and inference/serving.
• Accelerate AI workloads including agent planning, tool-use, and code generation.

Requirements

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

Nice to Have

• Strong experience building/evaluating deep learning models, coding agents, and developer tooling.
• Ability to optimize and deploy high-performance models, including on resource-constrained platforms.
• Proven GPU performance optimization (e.g., benchmark wins or published results).
• Publications or open-source leadership in deep learning, multi-agent systems, reinforcement learning, or AI systems.