Nsight Systems Jobs

Aleph Alpha is seeking a Senior Performance Engineer to join their pre-training efficiency team in Heidelberg. This role focuses on optimizing the systems required to train foundation models at scale, aiming to maximize hardware utilization and training throughput on large-scale GPU clusters. You will work at the intersection of deep learning frameworks, distributed systems, and GPU microarchitecture to eliminate bottlenecks from the Python layer down to the GPU kernel. The team fosters a culture of ownership, autonomy, and empowerment, with a flat organizational structure that enables quick decision-making and open communication.

SF Tensor is building the future of high-performance compute for AI by rethinking and rebuilding the entire stack, from hardware to cloud. We aim to eliminate the friction that slows down AI development, making compute faster, cheaper, and more accessible. Our Kernel Optimizer automatically finds the fastest code for any hardware, and our Model Foundry manages workloads across clouds and chips. We are backed by leading investors and are seeking individuals passionate about advancing AI through compute innovation.

$285k - $315k

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.