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Open nowPosted 129 days ago

后训练工程师

dx3a2bminsq/index64 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now后训练工程师dx3a2bminsq/index · 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 dx3a2bminsq/index's own form.

The reply lands in your private mailbox

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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. dx3a2bminsq/index 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. 58.1%60 days
This job: posted 129 days ago

dx3a2bminsq/index median: 1 days open

The posting

1、负责VLA/多模态大模型后训练方法的探索与研究，包括监督微调、RLHF、RLVR、DPO等对齐技术的算法改进与创新； 2、设计并实现高效的后训练实验框架，探索不同后训练策略对模型泛化性、鲁棒性及任务成功率的影响规律； 3、研究模型在具身任务中的行为对齐问题，包括指令遵循、安全约束、偏好对齐等，推动模型行为更符合真实场景需求； 4、探索自动化后训练数据构建方法，包括高质量指令数据的生成、筛选与增强，降低后训练对人工标注的依赖； 5、跟踪CoRL、ICRA、NeurIPS等顶会中具身智能、后训练对齐相关方向的前沿进展，将有效算法快速实验验证并沉淀为团队技术资产； 6、建立后训练效果的评估体系，设计科学的评测基准与实验范式，量化分析不同后训练方法的优劣与适用边界。

1、计算机、人工智能、自动化、机器人等相关专业硕士及以上学历，博士优先； 2、3年以上深度学习或强化学习研究经验，有VLA/多模态模型训练或后训练项目经验者优先； 3、精通Python及PyTorch，熟悉DeepSpeed、Megatron等分布式训练框架，具备良好的工程实现能力； 4、深入理解RLHF、PPO、DPO等对齐算法原理，有相关算法实现或改进经验者优先； 5、熟悉大模型SFT、指令微调等技术，了解数据构建与质量对后训练效果的影响； 6、具备较强的科研能力与创新思维，能够独立提出并验证新的后训练方法； 7、在ICML、NeurIPS、ICLR、RSS、CoRL等顶会以第一作者发表过论文者优先； 8、具备良好的沟通表达与团队协作能力，能够与预训练、数据、评测等团队高效配合。

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