トレンド企業

Tesla
Tesla

Accelerating the world's transition to sustainable energy.

Sr. Mechanical Design Engineer, Automated Test Equipment

職種エンジニアリング
経験シニア級
勤務地Richmond Hill, Ontario
勤務オンサイト
雇用正社員
掲載今日
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What To Expect
We are looking for a highly motivated and hands-on Sr. Mechanical Engineer to join the Manufacturing Test Engineering team – part of the “machine that builds the machine.” This team designs and builds robust, data-driven test systems for Tesla’s power electronics used in vehicles, energy storage, charging solutions, and humanoid robots. The ideal candidate is detail-oriented, organized, and thrives in a fast-paced, high-responsibility environment. They take pride in hands-on problem solving, have strong analytical skills, and are eager to learn and share knowledge. This role requires flexibility and a willingness to travel both domestically and internationally to support equipment development, deployment, and collaboration with global teams. This position plays a key role in shaping the quality and performance of Tesla’s core technologies and is based in Toronto, Reno, or Palo Alto.

What You'll Do

  • Machine design of automated test equipment, which includes preparing detailed-level CAD models, pneumatic diagrams, and verifying designs using structural and thermal FEA, CFD, tolerance stack-up
  • Create detailed drawings and coordinate with vendors to fabricate custom machined parts, weldments, and sheet metal components
  • Selection and integration of commercial components, sensors, servos, pneumatic actuators, etc.
  • Lead conceptual equipment development and carefully balance product specifications, process requirements, layout complexity, cost, and lead-time limits
  • Review, identify, and provide feedback on performance, design simplicity, robustness, assembly, and installation
  • Support building, debugging, validation and equipment duplication efforts, and fine-tune equipment for release to production
  • Perform on-site and off-site acceptance testing (SAT/FAT) of test equipment


  • What You'll Bring

  • Degree in Mechanical Engineering, Robotics, Mechatronics Engineering, or equivalent experience
  • 5+ years of experience as Mechanical/Mechatronics/Automation Engineer with focus in automation, machine design, robotics, or product development
  • Versed in SolidWorks, PDM, and Ansys, or similar CAD/CAE software
  • Strong understanding of drafting standards and the application of GD&T (e.g., ASME Y14.5)
  • Knowledgeable in solid mechanics, pneumatics, hydraulics, dynamics, material selection, prototyping, testing methods, everyday machining, and fabrication processes
  • Exposure to a wide variety of test systems, production machinery, industrial sensors, actuators, and equipment (pogo-pins, pressure transducers, temperature controllers, current meters, etc.)


  • , Tesla

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    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

    10件のレビュー

    3.8

    10件のレビュー

    ワークライフバランス

    2.3

    報酬

    4.0

    企業文化

    3.2

    キャリア

    4.1

    経営陣

    2.8

    65%

    知人への推奨率

    良い点

    Innovative projects and cutting-edge technology

    Great team and supportive colleagues

    Good compensation and benefits

    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

    1,403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

    面接レビュー

    レビュー4件

    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