Platform Engineer
About the Job
Designs and develops cloud-native microservice components on Kubernetes
Builds monitoring and logging platforms for cloud-native applications
Designs and develops Software Development Kit (SDK) of Furiosa NPUs
Develops high-performance runtime system handling DNN inference requests
Develops ML production softwares to manage machine learning lifecycles
Develops internal tools and services that improve teams' productivity
Writes API references and development documents
HW 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 Qualifications
Bachelor’s degree in Computer Science or a equivalent work experience
Excellent communication skills for requirement gathering and clarification
3+ years strong programming skills in one or more of the following languages - Rust, Python, Golang, C++
Preferred Qualifications
2+ years experience developing cloud-native applications with Kubernetes
2+ years of experience building and managing microservices in AWS, Azure, GCP or Kubernetes
Experience with ML/DNN frameworks, e.g., Tensorflow, Pytorch, Apache MXNet
Knowledge of testing and CI/CD pipeline, e.g., Jenkins, and others
Experience developing high-performance and highly concurrent server applications
Experience with RDBMS, NoSQL systems and message queuing systems, such as Kafka, AWS SQS
Experience developing production-grade softwares for customers
Experiences in authentication & authorization methodologies, e.g., OpenID, JWT, OAuth, 802.1X, and others
Understanding of zero trust networks
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