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Open nowPosted 15 days ago

具身模型算法实习生

agirobot/internrecruitment367 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now具身模型算法实习生agirobot/internrecruitment · Shanghai, 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/internrecruitment'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/internrecruitment postings stay open a median of 2 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 15 days ago

agirobot/internrecruitment median: 2 days open

The posting

岗位职责 1. 参与 VLA 具身大模型的后训练研发，包括 SFT 数据构建、模型微调（LoRA / 全量）、训练超参调优与效果评测 2. 参与多模态数据 pipeline 建设：数据采集、清洗、标注方案设计与质量筛选，构建面向真实机器人场景的高质量训练数据集 3. 跟踪并复现 VLA / WAM 领域前沿论文与开源模型（如 RT-2、OpenVLA、π0、Diffusion Policy 等），输出技术调研报告与可运行的实验方案 4. 在仿真环境（Isaac Sim / MuJoCo 等）与真机平台上完成模型闭环验证：从策略训练到部署测试，参与 Sim2Real 迁移实验与效果分析 5. 参与评测体系建设：设计任务成功率、泛化性、鲁棒性等评测指标，搭建自动化评测工具链 6. 协助模型在机器人芯片上的推理优化与部署调试，参与推理延迟、吞吐量等性能瓶颈的定位与改进 任职要求 1. 计算机 / AI / 机器人 / 自动化等相关专业在读硕士或博士（优秀本科生亦可） 2. 扎实的深度学习基础，熟悉 Transformer 架构与多模态模型原理（视觉-语言联合建模、条件生成等） 3. 熟练使用 Python + PyTorch，有完整的模型训练、调优与实验管理经验（日志 / checkpoint / 消融实验等） 4. 了解至少一种主流 VLA 架构或动作生成方案（如 Diffusion Policy、Flow Matching、Action Tokenization 等） 5. 具备良好的英文文献阅读能力，能快速理解和复现顶会论文的核心方法 6. 每周 ≥4 天，连续 ≥6 个月 加分项 - 有 VLA / VLM / Diffusion 等模型的实际训练或微调经验（非仅调用 API） - 熟悉模仿学习（BC / ACT / Diffusion Policy）或强化学习（PPO / SAC）算法，有相关项目实践 - 有仿真环境使用经验（Isaac Sim / MuJoCo / ManiSkill / RoboSuite 等），了解 Sim2Real 迁移的基本方法 - 参与过具身智能 / 机器人操作相关项目（竞赛、实验室课题、开源贡献均可） - NeurIPS / ICML / ICLR / CoRL / ICRA 等顶会发表过相关论文

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