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Open nowPosted 10 hours ago

Model Quantization Expert

momenta/talent227 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen nowModel Quantization Expertmomenta/talent · 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 momenta/talent'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.

12.4% 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. 4.5%3 days
  3. 12.4%7 days
  4. 20.0%14 days
  5. 35.5%30 days
  6. 58.6%60 days
This job: posted 10 hours ago

The posting

1.负责智驾端到端大模型、世界模型的量化压缩工作,搭建并维户支持多种车端芯片的量化工具链,支撑模型规 模化部署。 2.结合智驾真实业务场景,设计落地性强的量化、蒸馏、剪枝等模型压缩方案,在压缩模型体积、提升推理速度 的同时,保障模型精度达到业务要求。 3.深度研究各类车规芯片的架构与端侧执行逻辑,搭建芯片仿真、精度对齐、性能评测体系,保障模型跨芯片稳 定运行。 4.针对INT8/INT4/FP4/混合精度等不同量化方案做全链路调优,解决量化误差、算子适配、分布式兼容等技术 难点,持续挖掘推理性能上限。 5.跟进行业前沿量化与模型压缩技术,沉淀标准化方案与最佳实践我,推动团队技术能力迭代。

1.计算机、电子信息、自动化等相关专业,本科及以上学历,有模型量化、端侧推理优化相关工作经验。 2.精通主流量化(PTQ/QAT)、模型蒸馏、剪枝等压缩算法,熟练掌握INT8/INT4/FP8/FP4等多精度量化方案 3.扎实的编程功底,熟练使用Python、C/C++,精通PyTorch框架,了解ONNX、推理引擎相关技术优先。 4.熟悉CNN、Transformer、BEV、DETR等视觉/智驾主流模型结构与原理,理解模型前向推理逻辑。 5.有车端芯片、边缘芯片适配经验,了解端侧NPU执行特性者优先;有智能驾驶模型量化落地经验者优先。 6.具备较强问题拆解与实战能力,乐于钻研技术,思路灵活、富有创新意识,具备良好的沟通协作能力。

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One press. We do the rest.

  1. A CV for this posting

    Written against momenta/talent'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 momenta/talent'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

    momenta/talent'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.
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3×

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  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

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