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求人Tesla

Test Engineer, Passive Safety (m/w/d)

Tesla

Test Engineer, Passive Safety (m/w/d)

Tesla

Kreisfreie Stadt Berlin

·

On-site

·

Full-time

·

Today

必須スキル

Excel

Jira

What To Expect
The Passive Safety Team plans, executes, analyzes, and reports on crash, sled, and component-level testing for vehicle development, regulatory certification, and consumer protection programs (e.g., Euro NCAP). We are constructing a new passive safety component test lab in Berlin, Germany; this position will primarily be responsible for pedestrian and interior impact, vehicle structure, and airbag deployment testing in this new laboratory.

What You'll Do

  • Collaborate in a team-based environment to commission new test equipment and lab capabilities. Execute airbag deployment, pedestrian and interior impact, and vehicle structural strength testing in our Berlin test lab.
  • Act as the passive safety technical expert on relevant test regulations and protocols, as well as lab equipment (including calibrations, data acquisition, and fixture validation).
  • Plan test programs, oversee execution, document setup details, analyze results, and report on incidents.
  • Lead projects to improve lab, equipment, and workflow quality and efficiency.
  • Design and build test fixtures to interface with Tesla vehicles.
  • Write and refine test procedures.
  • Partner with program managers, suppliers, and factory teams to plan and source necessary test samples.
  • Work with internal engineering teams to develop and validate the performance of vehicle passive safety systems.
  • Maintain safe working practices and a secure environment, prioritizing the safety of yourself and your colleagues.


  • What You'll Bring

  • Broad experience in automotive passive safety testing from an OEM or third-party test lab. Experience with Euro NCAP and ECE regulatory testing preferred.
  • Hands-on experience with battery electric vehicle (BEV) passenger vehicles; Tesla-specific experience a plus.
  • Proficiency in operating and diagnosing passive safety test equipment, such as data acquisition systems, coordinate measurement tools, high-speed cameras, launchers, deployment systems, and hydraulic test setups.
  • Strong computer skills for diagnostics and reporting (e.g., Microsoft Word, Excel, PowerPoint, Jira, and Tesla-specific diagnostic tools).
  • Excellent technical communication skills in English, both verbal and written, for collaborating with international teams.
  • Proactive mindset with a commitment to doing things right, adapting quickly to changes, and thriving in a fast-paced environment.
  • Ability to manage multiple priorities, organize workloads, and meet deadlines.
  • Bachelor’s of Engineering Degree or equivalent work experience.


  • , Tesla

    総閲覧数

    0

    応募クリック数

    0

    模擬応募者数

    0

    スクラップ

    0

    Teslaについて

    Tesla

    Tesla

    Public

    A financial leasing taxi company that provides vehicles to customers

    140,000+

    従業員数

    Ciudad De Panamá

    本社所在地

    $800B

    企業価値

    レビュー

    3.8

    10件のレビュー

    ワークライフバランス

    2.2

    報酬

    3.8

    企業文化

    3.5

    キャリア

    4.1

    経営陣

    2.8

    65%

    友人に勧める

    良い点

    Innovative projects and cutting-edge technology

    Great team and supportive colleagues

    Opportunities for growth and learning

    改善点

    Long hours and poor work-life balance

    High pressure and tight deadlines

    Management issues and high expectations

    給与レンジ

    1,398件のデータ

    Junior/L3

    Mid/L4

    Junior/L3 · Associate Analyst

    2件のレポート

    $94,875

    年収総額

    基本給

    $82,500

    ストック

    -

    ボーナス

    -

    $92,000

    $97,750

    面接体験

    4件の面接

    難易度

    3.5

    / 5

    期間

    14-28週間

    体験

    ポジティブ 0%

    普通 75%

    ネガティブ 25%

    面接プロセス

    1

    Application Review

    2

    Recruiter Screen

    3

    Technical Phone Screen

    4

    Take-home Assignment

    5

    Panel Interview

    6

    Offer

    よくある質問

    Coding/Algorithm

    Technical Knowledge

    Behavioral/STAR

    System Design

    Machine Learning Concepts