Our company is at the forefront of developing autonomous driving technology, which involves processing massive datasets collected by self-driving vehicles as they navigate real-world environments. These datasets are crucial for machine learning and algorithm testing. We utilize Kubernetes as the platform to run these processes. Our Cloud Platform team is responsible for deploying and maintaining Kubernetes clusters and related infrastructure in both cloud and on-premises (bare metal) environments.

We are seeking an engineer to join our efforts in developing and maintaining a Linux+Kubernetes platform for autonomous driving technology development. You will be tasked with finding innovative solutions to enhance the stability of Kubernetes with our specific workloads, and you will play a key role in deploying new sites both in the cloud and on-premises.

What You'll Do:

Support and develop large K8s clusters (each with over 100 nodes).
Dive into research on approaches to enhance the stability of Linux and K8s as platforms for big data processing tasks.
Participate in creating new on-premises and cloud installations.
Develop deployment tools for internal users.

What You'll Need:

Proficiency in coding with Python or Go at a middle developer level.
Experience using K8s at a user level, with the ability to deploy applications and diagnose issues.
Experience in administering production K8s clusters.
Understanding of the internal workings of K8s.
Familiarity with Infrastructure as Code tools and the GitOps approach.
Experience with cloud technologies.

Nice to Have:

Experience deploying K8s clusters from scratch.
Experience writing K8s operators.
In-depth knowledge of the Linux Kernel and network stack.
Familiarity with software-defined storage, such as Ceph.
Experience with GPU (Nvidia) virtualization technologies.

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