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Open nowPosted 34 days ago

优才-运动智能与博弈算法工程师

agirobot/campusrecruitment420 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now优才-运动智能与博弈算法工程师agirobot/campusrecruitment · 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 agirobot/campusrecruitment'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. agirobot/campusrecruitment 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 34 days ago

agirobot/campusrecruitment median: 1 days open

The posting

  • 负责复杂动态环境下的智能决策、规划与控制算法研发；
  • 研究强化学习、Multi-Agent RL、Self-Play、MCTS 等算法，并应用于机器人智能决策；
  • 构建状态预测、行为预测、策略规划与实时决策系统；
  • 负责 Hierarchical RL、Skill Learning、Motion Policy 等算法研发，实现高层决策与底层运动技能协同；
  • 搭建大规模仿真训练、评测及 Sim2Real 闭环；
  • 推动算法从仿真环境向真实机器人部署落地。
  • 计算机、机器人、自动化、控制等相关专业，本科及以上学历；
  • 扎实的强化学习、机器学习、规划或控制基础；
  • 熟悉 PPO / SAC / Multi-Agent RL / Self-Play / MCTS 等一种或多种算法；
  • 熟悉 Python、PyTorch，具备较强的算法工程能力；
  • 有机器人、游戏 AI、智能决策或复杂控制系统相关项目经验。

加分项

  • 有人形机器人 / 腿式机器人 RL 项目经验；
  • 有 Hierarchical RL、Skill Learning、Motion Imitation / Motion Diffusion 经验；
  • 有 Isaac Lab、MuJoCo、Brax 等仿真平台经验；
  • 有大规模 GPU 训练、Sim2Real 或真实机器人部署经验；
  • 有 Game AI、多智能体博弈、自博弈相关经验。
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  1. A CV for this posting

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  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/campusrecruitment's form

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

  4. Every reply, sorted

    agirobot/campusrecruitment'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

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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
  • Who got the interview, and who heard nothing

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