Inference Systems Engineer: Linux Kernel Test and Validation

About the role

Introducing Cedana

The Problem

Inference is increasingly the dominant GPU workload and GPUs remain scarce and expensive. Every cold start, idle replica, and node failure is throughput that reduces revenue per GPU/watt. Data centers are bottlenecked by power requirements and GPU availability. Inference providers are measured on tokens per GPU, latency under load, and uptime, yet the complexity of models, hardware, and operations is a continuous and evolving challenge. Cluster productivity directly determines margin, research output, and productivity per MW.

Cedana’s Solution

Cedana mission is to accelerate and expand the ROI of every GPU. We maximize inference performance, reliability, and throughput per GPU with a breakthrough form of real-time GPU virtualization. We capture the full state of a running GPU workload and can manipulate it in real-time to enabling full workload migration, throughput and power optimization, and more. The result is more tokens from the same GPUs, faster time to first token, higher availability, higher power efficiency. Our system operates at the kernel and CUDA driver level, requires no code or config changes, and works seamlessly with Kubernetes, SLURM, and NVIDIA Dynamo. We work with the leading inference providers, and we deploy into neoclouds, enterprises, and research clusters.

The Team

Cedana's founding team has spent over a decade making computation run fast, productively, and reliably for AI. Our team has PhDs and MS from Caltech, CMU, Cambridge University, and have published across NeurIPS, CVPR, and Nature. We published some of the earliest formal methods for guaranteeing convergence in distributed training. At Shopify, we've developed a control plane for robotics fleets used in warehouse automation. We bring repeat founder experience, having built and exited a Series B healthcare AI company.

Backed by Y Combinator, Initialized Capital, Pebblebed (founders of OpenAI and Facebook AI Research), Keith Adams (engineer #20 at VMware, founded HHVM and FAIR at Facebook, Chief Architect at Slack), Venture Guides, Garry Tan, and Gokul Rajaram.

More about Cedana

Cedana has secured partnerships with established AI / HPC systems integrators and OEMs, is in production with leading inference providers, research institutions and enterprises. Check out our co-published work with NVIDIA and measured results on 3rd party benchmarks.

The Role

What you’ll own

You will own the core components of our inference virtualization stack including production, test and validation for kernel development. This includes measurement and optimization. Over time, you will contribute to critical core components of our system, with a focus on new capabilities, performance, and reliability.

What You'll Do

- Monitor and ensure regressions: Quantifying regressions to ensure our development cycle is converging to clearly specified objectives.

- Automate and validate testing: A key priority is to understand and extend our testing platform to establish your understanding of how our system works. Ensure testing is complete, all tests are passing, and our environments match our customers. Reliability and testing is a key part of our culture and you will push our bar higher.