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Tesla
Tesla

Accelerating the world's transition to sustainable energy.

Vehicle Dynamics Modeling Engineer, Simulation Infrastructure

직무머신러닝
경력미들급
위치Richmond Hill, Ontario
근무오피스 출근
고용정규직
게시오늘
지원하기

필수 스킬

Python

Rust

Machine Learning

What To Expect
As a Vehicle Dynamics Simulation & Data Analysis Engineer at Tesla, you will be at the forefront of developing the tools that define the performance of our next-generation vehicles. This role is a unique opportunity to merge your passion for vehicle dynamics, software development, and data science to directly impact products that accelerate the world's transition to sustainable energy.

You will be a key contributor to our advanced simulation toolchain, working from first principles to model complex vehicle behaviors. Your expertise will be crucial in transforming vast amounts of simulation and real-world test data into actionable insights that drive engineering decisions. This position requires a meticulous, data-driven engineer who thrives in a fast-paced, collaborative environment and is committed to solving the most challenging problems in vehicle performance.

What You'll Do

  • Architect, develop, and maintain a world-class vehicle simulation toolchain for both offline analysis and driver-in-the-loop (DIL) simulator applications
  • Develop and maintain robust data pipelines to process, analyze, and visualize terabytes of data from simulations, track testing, and our global vehicle fleet
  • Apply statistical analysis and machine learning techniques to correlate simulation models with real-world performance data, identifying key performance indicators and areas for improvement
  • Create intuitive data visualization dashboards and tools to provide actionable insights to vehicle dynamics, controls, and hardware engineering teams
  • Collaborate closely with vehicle development engineers to define requirements, develop new model features, and ensure simulation accuracy
  • Troubleshoot complex issues within the simulation ecosystem and lead data-driven correlation efforts to enhance predictive accuracy


  • What You'll Bring

  • Degree in Mechanical Engineering, Computer Science, or related field, or equivalent experience
  • Minimum of 2 years of experience in motorsport, automotive, or software development environments
  • Strong proficiency in Python for data analysis with libraries like Pandas, NumPy, and SciPy, and familiarity with at least one systems programming language such as C++, Rust, or C
  • Proven experience analyzing large datasets to derive engineering insights
  • Solid understanding of vehicle dynamics principles and practical experience with vehicle hardware and suspension components
  • Demonstrated work ethic, integrity, and ability to manage multiple priorities in a dynamic environment


  • , 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

    Senior/L5

    Junior/L3 · Data Annotation Specialist

    373개 리포트

    $49,465

    총 연봉

    기본급

    $49,465

    주식

    -

    보너스

    -

    $35,995

    $67,975

    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