招聘
必备技能
Python
Machine Learning
Tesla is building robust embodied intelligence through autonomous driving and humanoid robots. Core to reaching this goal is developing intelligent agents that see, move, and speak in the real world. In this role, you’ll architect and deploy models that allow our agents to listen, understand, and respond in real time powered by our custom AI chip on our embodied products. Your work will be central to making Optimus or our cars as seamless as talking to a friend. Most importantly, you will see your work repeatedly shipped to and utilized by thousands of Humanoid Robots in real world applications and millions of cars.
What You'll Do
Compensation and Benefits
Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:
$176,000 - $420,000/annual salary + cash and stock awards + benefits
Pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
, Tesla
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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
Senior/L5
Junior/L3 · Data Annotation Specialist
373份报告
$49,465
年薪总额
基本工资
$49,465
股票
-
奖金
-
$35,995
$67,975
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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