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Open nowPosted 44 days ago

VLA算法工程师-HK

agirobot/referral515 open roles

Where
Hong Kong (China), Hong Kong Island, Hong Kong, China
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Your applicationOpen nowVLA算法工程师-HKagirobot/referral · Hong Kong (China), Hong Kong Island, Hong Kong, China

  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.

12.1% 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. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 44 days ago

agirobot/referral median: 1 days open

The posting

1. 与各地算法团队联合，共同定义操作策略模型的技术方案；负责其中模型结构、预训练或后训练方向的方案设计与实现； 2. 跟踪 VLA / VLM 领域前沿进展，引入并复现有价值的新方法，针对当前方法的不足提出改进与创新方案，并推动其进入开发主线； 3. 围绕成功率、泛化性与推理效率持续优化策略模型，输出可复现的训练流程、模型与评估报告； 4. 在真机上完成算法验证与迭代，配合工程团队推进产品化落地，参与真机问题的定位与闭环； 5. 应用场景：全身 VLA 操作、灵巧操作、高动态反应式操作；与仿真及数据团队协作定义训练数据规范与质量标准，参与数据问题的定位与闭环； 6. 分为 VLA 基础模型结构、强化学习预训练、强化学习后训练三个方向，按候选人背景匹配。

1. 硕士及以上学历，计算机、人工智能、机器人、自动化等相关专业； 2. 掌握机器学习、最优化、机器人学的基础理论； 3. 熟练使用 Python，具备良好的编程规范与工程习惯，熟悉 PyTorch 及分布式训练工具链； 4. 深入了解 VLA、VLM 及图像 / 视频生成模型，具备 VLA 或 VLM 的完整训练经验（数据构建—训练—评估—迭代）； 5. 对数据质量有深刻理解，能够从模型表现反推数据问题； 6. 分方向要求： 1. 基础模型结构方向：熟悉主流 VLA 架构（Diffusion Policy、Flow Matching、Autoregressive Action Tokenization 等），有模型结构改进与消融实验经验； 2. 强化学习预训练方向：熟悉大规模离线数据上的表征学习与预训练范式，有 World Model 或 Offline RL 相关经验； 3. 强化学习后训练方向：熟悉在线微调、奖励建模、RLHF / RLAIF 等后训练方法，有仿真或真机闭环调优经验； 7. 有机器人控制或真机部署经验者优先；了解机器人行业及实际落地约束；

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