CUTLASS Jobs

SpaceXSI is building one of the world's largest AI supercomputers from the ground up. As part of the Compute Infrastructure team, you will own both the raw GPU supercomputer and the platform layer that runs on top of it. You will work across the full stack—from low-level GPU kernel optimizations and Linux kernel internals to massive-scale orchestration and virtualization—to make training and inference at SpaceXSI as fast, reliable, and scalable as possible. This is a broad, high-impact role that combines hardcore supercompute and compute infrastructure work. Your contributions will directly accelerate Grok's training speed and overall AI progress.

$180k - $440k

We are a dedicated research lab focused on building, understanding, using, and risk-managing foundation models. Our mission is to advance research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy. As part of our team, you will work on the core of cutting-edge foundation model training alongside world-class researchers, data scientists, and engineers. You will tackle fundamental and impactful challenges in AI development, contributing to groundbreaking AI solutions that have the potential to reshape entire industries. Strategic and innovative problem-solving skills are essential for establishing our institution as a global hub for high-performance computing in deep learning.

$150k - $450k

Liquid AI, a rapidly scaling company spun out of MIT CSAIL, is developing general-purpose AI systems designed for efficient deployment across various hardware, from data centers to edge devices. We focus on delivering low latency, minimal memory usage, privacy, and reliability for enterprise clients in sectors like consumer electronics, automotive, life sciences, and financial services. We are seeking exceptional individuals to join our small, fast-moving, high-ownership team to tackle complex performance challenges that generic frameworks cannot address.

Genmo is a research lab developing advanced video world models to understand, simulate, and interact with the physical world, aiming to unlock the right brain of AGI. We are seeking a GPU Performance Engineer to optimize our model serving stack and extract maximum performance from our H100 infrastructure. This role involves identifying bottlenecks, implementing solutions for significant speedups, and pushing hardware to its theoretical limits, with a focus on microsecond optimizations.

Magic is seeking a Kernel Engineer to design, implement, and maintain high-performance kernels that optimize throughput and latency for AI model training and inference. This role is crucial for supporting Magic's long-context windows, which present unique challenges in memory utilization, data movement, and sustained throughput. You will be responsible for the entire lifecycle of kernel development, from design and implementation to deployment and ensuring production reliability.

$275k - $550k