Compiler Engineer - AI Inference

Drive technical innovation: Participating in hands-on development focusing on kernel generation and computational graph optimizations for next-generation NVIDIA GPUs.

Advance the state-of-the-art: Solve complex compilation problems for AI workloads (both inference and training) and successfully transition these breakthroughs into enterprise and consumer products.

Collaborate on hardware/software co-design: Partner with leading experts across our software, hardware, and research divisions to architect and co-design future silicon.

Scale AI to the datacenter: Participating in the advancement and optimization of datacenter-scale AI workload deployments.

BS or MS in Computer Science, Computer Engineering, or a related field (or equivalent experience). A PhD is strongly preferred.

Compiler Experience: 3+ years of relevant industry experience specializing in compiler optimizations, synthesis, and placement.

MLIR Knowledge: Demonstrated, hands-on experience working with MLIR.

Programming Excellence: Exceptional C/C++ and Python programming and software design skills, including rigorous debugging, performance analysis, and test design.

Team Dynamics: Strong communication and interpersonal skills, with the ability to collaborate effectively in a dynamic, fast-paced, and product-oriented environment.

Hardware Implementation: Hands-on experience implementing complex AI workloads on CPU, GPU, and/or custom AI accelerator architectures.

LLM Knowledge: Deep understanding of Large Language Model (LLM) inference and its profound implications on computer architecture.