About the job
About Us
At ChipStack, we stand at the forefront of the technological revolution, aiming to transform the design of silicon chips which are pivotal in today's tech-centric landscape. While their complexity has surged due to rising performance requirements from applications such as AI, the methods used for their design have remained stagnant for decades. We are determined to innovate and lead this change.
Our team is dynamic, highly skilled, and operates with agility. We are comprised of experts with experience at leading technology companies including Qualcomm, Nvidia, Google, Meta, and the Allen Institute for AI. Supported by premier investors such as Khosla Ventures, Cerberus, and Clear Ventures, we have already partnered with over 10 pioneering clients, ranging from Fortune 100 giants to ground-breaking AI silicon startups.
About This Role
This position offers an exceptional opportunity to join the founding team at ChipStack, where we are redefining the approach to modern silicon chip design. Collaborating with seasoned chip designers, machine learning scientists who have successfully trained large language models (LLMs) at scale, and top-tier infrastructure and software engineers, you will leverage your expertise in ML and data infrastructure to tackle some of the most challenging problems in chip design.
About You
You thrive in a startup environment, drawn by the energy and dynamism it provides. You are committed to delivering outstanding customer experiences, willing to go the extra mile to ensure satisfaction. Self-motivated and driven, you possess a strong sense of urgency and the ability to work independently with minimal guidance. You welcome complex problems and relish the opportunity to explore uncharted territories.
This Role
We seek a skilled and experienced ML Infrastructure Engineer to join our founding team. The ideal candidate will have a solid background in designing and scaling ML infrastructure and training pipelines. Your primary responsibility will be to construct the foundational infrastructure that supports the training, fine-tuning, evaluation, and deployment of LLMs in both cloud and on-premise environments. Your contributions will significantly enhance our product capabilities and accelerate our iteration processes.
