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Open nowPosted 47 days ago

机器人运控与本体性能专家

agirobot/referral515 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now机器人运控与本体性能专家agirobot/referral · Shenzhen, Guangdong, 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 agirobot/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.

12.3% of postings close within 7 days. Measured by our own scanner across the market. agirobot/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. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: posted 47 days ago

agirobot/referral median: 1 days open

The posting

  • 负责机器人运控问题分析与定位，针对稳定性、抖动、跟踪误差、落地冲击、极限动作失败等问题进行系统诊断。
  • 分析电机、减速器、关节、结构、传感器、通讯及控制链路等硬件能力与性能边界，识别影响运控效果的关键瓶颈。
  • 结合算法与硬件特性，提出本体改制、参数优化及硬件性能提升建议，推动问题闭环。
  • 针对实际问题提出运控算法改进方案，包括力矩控制、全身控制、状态估计、轨迹跟踪、抗扰及 Sim2Real 等。
  • 支持高动态动作、复杂运动及新本体导入，建立从问题分析、实验验证到改制/算法优化的完整闭环。
  • 机器人、自动化、控制、机械、机电等相关专业硕士及以上学历。
  • 熟悉机器人动力学、运动学、力矩控制、状态估计、WBC/MPC 等运控基础技术。
  • 熟悉电机、驱动器、减速器、编码器、IMU 等核心硬件，能够理解硬件参数对运控性能的影响。
  • 具备较强的真机问题分析和系统 Debug 能力，能够区分算法、硬件、结构及系统链路问题。
  • 有人形机器人或高动态机器人实际研发、调试和落地经验优先。

加分项 - 有机器人本体改制、关节性能优化、力矩跟随及结构优化经验。 - 有高动态运动、强化学习运控、Sim2Real 或全身控制经验。 - 熟悉 EtherCAT/CAN、实时控制系统及机器人底层软硬件链路。 - 有从“现象分析 → 根因定位 → 改制/算法方案 → 真机验证”完整项目经验者优先。

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One press. We do the rest.

  1. A CV for this posting

    Written against agirobot/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.

  3. We apply on agirobot/referral's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

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

  4. Every reply, sorted

    agirobot/referral's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

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

  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
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Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

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The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

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