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Tesla
Tesla

Accelerating the world's transition to sustainable energy.

Site Reliability Engineer, Platform Engineering

직무DevOps
경력미들급
위치Pune, Maharashtra, India
근무오피스 출근
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필수 스킬

Python

AWS

Kubernetes

Terraform

Linux

Position Description

Tesla's Platform Engineering is looking for a Site Reliability Engineer to join our team. As a member of the team, you will be building and maintaining Kubernetes clusters using infrastructure-as-code tools like Ansible, Terraform, ArgoCD and Helm and helping the application teams to be successful on our platform. The underlying infrastructure is a mix of on-premise VMs, bare metal hosts and public clouds such as AWS located all around the globe, which presents unique challenges and opportunity to work with different types of infrastructure technologies. A successful candidate will be expected to possess expert knowledge in Linux fundamentals, architecture and performance tuning; as well as software development skills to match. Experience running Kubernetes in production will be a strong plus; we prefer Golang or Python for any automation or tools we have to build along the way. We are the team that runs production critical workloads for every aspect of the business at Tesla and sets the standards for other teams, a group of well-rounded generalists that not only solve the hardest problems in the industry but also push other Engineering teams at large to be better. Join us to get a chance to work with some of the best Engineers in the industry for one of the most transformative companies in the history of both automotive and energy industries.


Responsibilities

  • Hands-on with developers to deploy the applications to provide support
  • Building new features to improve the platform in terms of stability & updates 
  • Manage our Kubernetes clusters on-prem and in the cloud to support our growing workloads
  • Participating in the architecture design process and troubleshooting of live applications with the product teams 
  • Participating in a 24x7 on-call rotation
  • Influence architectural decisions with focus on security, scalability and high-performance 
  • Setup and maintain monitoring, metrics & reporting systems for fine-grained observability and actionable alerting 
  • Authoring technical documentation for workflows/processes/best practices


Requirements

  • Experience managing web-scale infrastructure in a production *nix environment
  • Ability to prioritize tasks and work independently with an analytical mind with a bias for action
  • Advanced or expert-level Linux administration and performance tuning skills
  • Bachelor's Degree in Computer Science, Computer Engineering, or equivalent experience or evidence of exceptional ability
  • Advanced experience with configuration management systems such as Ansible, Terraform or Puppet 
  • Demonstrable knowledge of the Linux operating system internals, networking stack, filesystems, resource scheduling and process management 
  • Exposure to AWS, or other cloud infrastructure providers
  • Experience managing container-based workloads, using Kubernetes or other orchestration software in production (ArgoCD, Helm)
  • Proficiency in a high-level language like Python, Go, Ruby and/or Java

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Tesla 소개

Tesla

Tesla

Public

A financial leasing taxi company that provides vehicles to customers

140,000+

직원 수

Ciudad De Panamá

본사 위치

$800B

기업 가치

리뷰

10개 리뷰

3.8

10개 리뷰

워라밸

2.3

보상

4.0

문화

3.2

커리어

4.1

경영진

2.8

65%

지인 추천률

장점

Innovative projects and cutting-edge technology

Great team and supportive colleagues

Good compensation and benefits

단점

Long hours and poor work-life balance

High pressure and tight deadlines

Management issues and high expectations

연봉 정보

1,403개 데이터

Junior/L3

Mid/L4

Junior/L3 · Associate Analyst

2개 리포트

$94,875

총 연봉

기본급

$82,500

주식

-

보너스

-

$92,000

$97,750

면접 후기

후기 4개

난이도

3.5

/ 5

소요 기간

14-28주

경험

긍정 0%

보통 75%

부정 25%

면접 과정

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Take-home Assignment

5

Panel Interview

6

Offer

자주 나오는 질문

Coding/Algorithm

Technical Knowledge

Behavioral/STAR

System Design

Machine Learning Concepts