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Open nowPosted 12 days ago

仿真测试工程师

li/referral788 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now仿真测试工程师li/referral · Beijing, Chinese Mainland

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on li/referral's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. li/referral postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 12 days ago

li/referral median: 1 days open

The posting

基于实车路测数据开展问题分析与根因定位，针对问题特点选择开环、闭环等评测方式，构建评测数据集与仿真场景，并建设场景干预、场景泛化、长尾场景生成及评估能力； 面向端到端自动驾驶架构，兼顾感知、预测、规划等模块，构建并持续优化覆盖安全、舒适、效率和导航的评估体系，快速识别算法变更引入的性能回退与异常； 运用仿真可靠性评估方法与工具，量化版本差异，分析结果不一致问题，并形成算法、仿真及产品团队易于理解的指标与结论； 构建基于 AI Agent 的自动化评测体系，覆盖数据质检、结果分析与问题归因，自动生成可追溯的评测报告和结论，提升评测效率与一致性。

计算机、自动化、车辆工程、统计学等相关专业硕士及以上学历，具备自动驾驶仿真测试或相关领域经验； 熟练掌握 C++ 和 Python，熟悉 Pandas、NumPy 等数据处理工具及脚本开发，熟悉 Shell 和 Git，能够在 Linux 环境下独立处理批量任务与日志； 深入理解 LogSim、WorldSim 仿真范式，具备实际工程落地能力； 理解自动驾驶评测指标体系（ADE/FDE、场景通过率、MPI 等），具有评测方案从 0 到 1 的落地经验； 了解自动驾驶端到端模型和 VLA 模型的基本原理，具备算法和传感器相关背景知识； 具备统计分析意识，能在分析过程中合理考量样本量、分布差异与噪声问题，具备较强的问题定位与解决能力。

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    Written against li/referral's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

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    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

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    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

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  6. The interview in your calendar

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    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
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  • Which posting, which company, which city
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That is how we know which CVs get called.

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