Platform Engineer

About The JobDesigns and develops cloud-native microservice components on KubernetesBuilds monitoring and logging platforms for cloud-native applicationsDesigns and develops Software Development Kit (SDK) of Furiosa NPUsDevelops high-performance runtime system handling DNN inference requestsDevelops ML production softwares to manage machine learning lifecyclesDevelops internal tools and services that improve teams' productivityWrites API references and development documentsHW operation tools for hyper scale datacenter, e.g. monitoring, dashboard, workbench, job scheduling server, HW resource management system, and others.Work on various operation tools, such as chip monitoring systems and multi-machine resource management and scheduling systems.Minimum QualificationsBachelor’s degree in Computer Science or a equivalent work experienceExcellent communication skills for requirement gathering and clarification3+ years strong programming skills in one or more of the following languages - Rust, Python, Golang, C++Preferred Qualifications2+ years experience developing cloud-native applications with Kubernetes2+ years of experience building and managing microservices in AWS, Azure, GCP or KubernetesExperience with ML/DNN frameworks, e.g., Tensorflow, Pytorch, Apache MXNetKnowledge of testing and CI/CD pipeline, e.g., Jenkins, and othersExperience developing high-performance and highly concurrent server applicationsExperience with RDBMS, NoSQL systems and message queuing systems, such as Kafka, AWS SQSExperience developing production-grade softwares for customersExperiences in authentication & authorization methodologies, e.g., OpenID, JWT, OAuth, 802.1X, and othersUnderstanding of zero trust networksContactrecruit@furiosa.ai