招聘

Sales Engineer (Technical Solutions Engineering), Megapack, Energy
Alexandria, New South Wales
·
On-site
·
Full-time
·
Today
必备技能
Excel
The Tesla Energy team is fast-paced and committed to enabling the energy transition. The Sales Engineering team operates at the centre of Tesla technology, business development and the deployment of utility scale Tesla energy projects.
We are seeking a technically-oriented Sales Engineer, with strong electrical engineering fundamentals, to help evaluate and define new utility scale Energy Storage Product projects and work to refine the customers requirements and deploy Tesla’s product against them. You will utilize engineering first principles and actively engage with customers to understand their requirements, leveraging your technical expertise and soft skills to build strong relationships and shape customized solutions.
As a key member of the team, you will help shape the success of projects in various applications across Australia, APAC and globally. You must have a genuine passion for engineering products that fundamentally change the world’s energy infrastructure and a desire to work in a fast-paced, entrepreneurial environment.
This is a full-time position that can be based in Sydney, Melbourne or Brisbane.
What You'll Do
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关于Tesla

Tesla
PublicA financial leasing taxi company that provides vehicles to customers
140,000+
员工数
Ciudad De Panamá
总部位置
$800B
企业估值
评价
3.8
10条评价
工作生活平衡
2.2
薪酬
3.8
企业文化
3.5
职业发展
4.1
管理层
2.8
65%
推荐给朋友
优点
Innovative projects and cutting-edge technology
Great team and supportive colleagues
Opportunities for growth and learning
缺点
Long hours and poor work-life balance
High pressure and tight deadlines
Management issues and high expectations
薪资范围
1,398个数据点
Junior/L3
Mid/L4
Junior/L3 · Associate Analyst
2份报告
$94,875
年薪总额
基本工资
$82,500
股票
-
奖金
-
$92,000
$97,750
面试经验
4次面试
难度
3.5
/ 5
时长
14-28周
体验
正面 0%
中性 75%
负面 25%
面试流程
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Take-home Assignment
5
Panel Interview
6
Offer
常见问题
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
System Design
Machine Learning Concepts
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