Platform Engineer

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.

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++

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

[email protected]