Skip to content
CV Rocket
Get started
How it worksThe enginePricingBlogContactSign in

Open nowPosted 20 days ago

大模型 / 多模态模型架构研究工程师实习生

icnal2nuefj7/0971036 open roles

Where
Beijing, Chinese Mainland
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen now大模型 / 多模态模型架构研究工程师实习生icnal2nuefj7/097103 · 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 icnal2nuefj7/097103'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.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.5%14 days
  5. 35.5%30 days
  6. 45.1%60 days
This job: posted 20 days ago

The posting

岗位职责 -研究和优化 Attention、MoE、Expert Routing、模型层数、宽度、连接结构等。 -设计和实现 checkpoint 权重迁移、Model Surgery、Expert Pruning/Merging、Layer Mapping 等方案。 -通过 Continued Pretraining、Knowledge Distillation 等方式，使新架构快速继承原模型能力。 -修改和调试 Transformers、Megatron、DeepSpeed/FSDP 等大模型训练代码。 -评估新架构在模型效果、训练成本、推理速度、显存占用等方面的收益。

技能要求 -熟练掌握 PyTorch，能够独立修改大模型网络结构和 forward 逻辑。 -深入理解 Transformer、Attention、MoE、GQA/MLA、RoPE、RMSNorm 等模型结构。 -熟悉大模型 checkpoint、state_dict、参数初始化和权重转换。 -有大模型预训练或 Continued Pretraining 经验。 -熟悉 FSDP、DeepSpeed、Megatron 等至少一种分布式训练框架。 -能够独立完成“架构设计 → 权重迁移 → 训练 → 评测 → 分析”的完整实验流程。 -研究和优化 Vision Encoder、Vision Attention、Patch Embedding、Patch Merger / Projector 等视觉模型结构。 -研究 Image / Video Token Compression、Vision-Language Alignment 及多模态信息融合机制。 -基于已有多模态模型 checkpoint，对 Vision Encoder、Projector 及 Language Model 进行联合架构改造和权重迁移。 -研究如何在降低视觉 token 数量和多模态计算成本的同时，保持或提升 OCR、图像理解、视频理解等能力。

加分项 -有 7B/30B/100B+ 模型训练经验。 -有 MoE、Sparse Attention、Linear Attention 等架构研究经验。 -做过 Model Surgery、模型裁剪、Expert Merge、Knowledge Distillation。 -修改过 Transformers / Megatron 核心源码。 -熟悉 CUDA、Triton、FlashAttention 或大模型性能优化。 【我们希望你具备】 不仅会调用模型和做 Fine-tuning，而是能够真正深入到： 模型架构、参数权重和训练 Dynamics 层面，研究如何在最大程度复用已有 checkpoint 的基础上，开发更高效的新模型架构。

From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against icnal2nuefj7/097103's own wording, from every piece of relevant proof in your profile.

  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 icnal2nuefj7/097103's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

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

  4. Every reply, sorted

    icnal2nuefj7/097103'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

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

Get the CV for this job
By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.