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Tesla
Tesla

Accelerating the world's transition to sustainable energy.

Sr. Electrical Engineer, Automated Test Equipment

직무엔지니어링
경력시니어급
위치Richmond Hill, Ontario
근무오피스 출근
고용정규직
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What To Expect
We seek a highly motivated and hands-on engineer with an electrical engineering background for a position in the Manufacturing Test Engineering group, a team focused on building robust, beautiful, data-centric automated testing equipment for Tesla’s power electronics and battery manufacturing lines. This team concentrates on mechanical, electrical, software, and controls of capital equipment for our production lines around the world. This is an exciting opportunity to be a part of the “machine that builds the machine,” working tightly with power electronics product design and manufacturing.

The ideal candidate takes pride in their hands-on work, analytical ability, communication skills and attention to detail. They look forward to learning an incredible amount on the job and carrying responsibility within the team.

What You'll Do

  • Architect novel, fully automated testing machinery from first principles, balancing cost, lead time, complexity, and test coverage across disciplines
  • Develop test specifications and break down requirements into a detailed execution plan while mentoring/advising more junior engineers on sub-system implementation
  • Research and specify electrical test equipment such as measurement equipment, power supplies, sensors, I/O devices, and other hardware to meet test requirements
  • Design schematics and layout for industrial electrical control panels which are NFPA79/NEC/UL508A compliant and review more junior engineers’ designs
  • Implement and validate reliable industrial safety systems (OSHA, ISO standards compliant) to safeguard high voltage and mechanical hazards
  • Debug/optimize automated processes to minimize cycle time and maximize uptime
  • Perform bench testing on electrical components to validate test processes
  • Develop PLC sequences in Allen Bradley and Siemens for automated test machinery
  • Domestic and international travel up to 20%


  • What You'll Bring

  • Capable of specifying electrical test equipment including but not limited to power supplies, multimeters, oscilloscopes, and power analyzers
  • Proficiency building complex machine schematics in EPLAN, AutoCAD Electrical, or similar electrical CAD software
  • Experience programming Programmable Logic Controllers (PLCs), preferably in Rockwell Allen Bradley Studio 5000 and/or Siemens TIA Portal
  • Exposure to automation in an industrial/manufacturing environment
  • Exposure to high voltage power electronics (inverters, DC-DC converters, etc...)
  • Degree in Electrical or Mechatronic Engineering, or equivalent experience
  • 5+ years of hands-on controls/mechatronics/test/automation engineering experience


  • , Tesla

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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