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Open nowPosted 9 days ago

大模型训练算法实习生

agirobot/internrecruitment367 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now大模型训练算法实习生agirobot/internrecruitment · 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/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.

11.8% 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. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 9 days ago

agirobot/internrecruitment median: 2 days open

The posting

面向具身智能 / 人形机器人场景,在导师指导下参与大模型(LLM / VLM / VLA)的数据构建、微调训练与评估实验,通过真实项目积累大模型训练实战经验。核心看点是深度学习与大模型基础扎实、动手跑实验能力强、学习速度快。 有量化或端侧部署经验者加分。

岗位职责 数据构建:协助多模态(视觉 / 语言 / 动作)训练数据的清洗、合成、格式转换与质检;参与 SFT / 偏好数据集的构建,探索数据配比对效果的影响。 模型训练与微调:在已有训练框架基础上,开展 SFT、LoRA / QLoRA、DPO 等微调实验;跟踪 loss 与指标,分析收敛、过拟合等问题,整理实验结论。 评估体系:协助搭建评测集与自动化评测脚本,对比不同数据 / 超参 / 训练策略的效果,输出分析报告。 小模型与压缩探索(加分方向):在兴趣与时间允许下,尝试蒸馏、量化(GPTQ / AWQ 等现成工具)和端侧推理(llama.cpp / ONNX Runtime / TensorRT)的小实验。 工具与文档:编写训练 / 评测辅助脚本,整理实验记录与技术文档。

岗位要求 计算机 / 自动化 / 电子 / 数学等相关专业,2028 届本科 / 硕士 / 博士在读(毕业时间 2028 年)。 熟悉 Python,熟练使用 PyTorch;了解 Hugging Face Transformers 等常用生态。 掌握深度学习基础:Transformer、Attention、Tokenizer、Embedding、Loss 与优化器等基本原理。 至少有以下一项经历即可:课程 / 课题 / 竞赛 / 个人项目中训练或微调过模型(不限规模,小模型亦可);用 LoRA 等方法微调过开源大模型;读过并尝试复现过大模型相关论文或开源项目。 实习时间:每周 4 天及以上,连续 3 个月及以上,可尽快到岗。

加分: 训练侧:有 LLM / VLM / VLA 微调实战;了解分布式训练(DeepSpeed / FSDP);了解 RLHF / DPO;有可复现成果。 量化 / 端侧:了解或用过模型量化(INT8 / INT4、GPTQ、AWQ);有 TensorRT / ONNX / llama.cpp / MNN 等端侧推理经验;会 C++。

其他:熟悉 Linux / Git / Docker;有机器人 / 自动驾驶方向经历;有开源贡献、论文或竞赛获奖(非硬性)。

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