Senior Software Engineer, Infrastructure Join to apply for the Senior Software Engineer, Infrastructure role at CentML Senior Software Engineer, Infrastructure Join to apply for the Senior Software Engineer, Infrastructure role at CentML We are a small team with a big ambition of making modern machine learning accessible for everyone. At CentML, our mission is to enable anyone with an idea to deploy ML models without breaking the bank. We believe that modern AI will fundamentally transform how people work and live and we're here to help bring that future sooner. Our founding team is made up of experts in AI, compilers and ML hardware and has led efforts at companies like Amazon, Google, Microsoft Research, Nvidia, Intel, Qualcomm, and IBM. Our co-founder and CEO, Gennady Pekhimenko, is a world-renowned expert in ML systems with a publication history of top papers and multiple academic and industry research awards from Google, Amazon, and Facebook. Position Overview: We are seeking a highly motivated and skilled senior infrastructure engineer to join our team in a key role focused on designing, developing, and maintaining the CentML platform that offers a cost effective infrastructure for serving and training large scale machine learning models. As an infrastructure engineer, you will be responsible for laying out the design of a deployment infrastructure for ML training and inference jobs over GPU clusters that spans across multiple cloud service providers like AWS, GCP, Azure, Coreweave, and OCI. You should also be responsible for leading a team of engineers and building a scalable, performant, and reliable platform, enabling our customers to seamlessly access and utilize a comprehensive suite of ML services that we offer. Responsibilities: Design and lead the development of the deployment infrastructure of the CentML platform. The deployment infrastructure manages the hardware resources necessary to deploy the ML training and inference applications. Implementing GPU cluster scheduling solutions for large scale ML training and inference workloads to efficiently utilize the hardware resources in the GPU cluster. Communicate with our product teams and define new features and goals for improving the CentML platform. Qualifications: 4+ years of experience working with containerized deployment systems (e.g, kubernetes, openshift, terraform etc.). A big plus if you have contributed to kubernetes and have expertise in container runtime technologies like docker engine, containerd, or CRI-O Experience with deploying and managing cloud infrastructure on AWS, GCP, Azure Past experience in building GPU clusters for large scale ML training and inference is desirable. Knowledge in GPU architecture and Nvidia GPU virtualization technologies is highly desirable. Strong coding skills in languages like Python, Java, Go, and/or C/C++. An open and inclusive culture and work environment Twice a week free-lunch Full health and dental benefits Parental Leave top-up for 6 months Continuous education budget Generous vacation - we're not saying unlimited, but if you need extra time to recharge, just ask
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