主分类:AI训练推理与计算优化
来源 JD 数据(旧分类保留,当前主分类见上方)
{
"schema_version": "via_ai_product_manager_jobs_v1",
"data_type": "ai_product_manager_jobs",
"job": {
"job_title": "平头哥-深度学习推理引擎研发专家-杭州",
"job_level": "专家",AI生成
"work_category": "全职",AI生成
"department": "阿里集团",
"location": "杭州",
"work_mode": "未披露",AI生成
"job_category": "技术-芯片"AI生成
},
"company": {
"company_name": "平头哥",
"company_industry": "半导体 / 芯片设计",
"company_size": "未披露",
"company_website": "alibaba.com",
"company_description": "平头哥研发计算、存储及网络芯片,为人工智能基础设施提供支持。"
},
"compensation": {
"salary_range": {
"min": "",
"max": "",
"currency": "未披露",
"cycle": "未披露"
},
"benefits": "未披露"
},
"requirements": {
"working_years": 5,
"degree": "本科",
"language": "未披露",AI生成
"visa_support": "未披露",
"responsibilities": "1、参与设计和实现推理引擎SDK,提升推理性能、易用性和产品稳定性。(Design and develop inference engine。Focusing on performance、usability and product robustness)\n2、参与设计和实现推理引擎的AI编译。包括图融合、各类图优化、算子优化以及自动化调优等(Design and develop AI Compiling。including fusion,graph optimizations、kernel optimization and auto-tuning)\n3、参与设计和实现推理引擎的运行时系统。包括内存管理以及资源管理等等。实现高效和稳定的稳定性。(Design and develop runtime system,including memory management and resource management)\n4、参与设计和实现大模型的推理优化。基于推理引擎,研发和应用大模型推理优化的技术(Design and optimize LLM inference。Based on inference engine,develop and apply core technology for LLM inference)",
"requirements_text": "1、 CS/EE相关领域,5+年工作经验(A Masters or higher degree in Computer Engineering, Computer Science, Applied Mathematics or related computing focused degree (or equivalent experience), 5+ years of relevant software development experience)\n2、 熟悉C/C++编程(Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design).\n3、 熟悉深度学习框架,如Tensorflow,Pytorch(Familiar with deep learning framework,tensorflow or pytorch etc)\n4、 有较强的技术热情,自我驱动(Proactive and able to work without supervision)\n5、 具备下述条件优先:\na)有AI编译或推理引擎相关研发经验。(Related experience on deep learning compiling or inference engine)\nb) 熟悉CPU/AI架构并有深度学习系统研发经验(Prior experience with performance modelling, profiling, and code optimization in DL)\nc) 熟悉TensorRT、MLIR并跟踪行业技术趋势(Experience on TensorRT or MLIR is highly preferred)",
"skills": [AI生成
"C++",
"PyTorch",
"TensorFlow",
"深度学习",
"C语言"
],
"preferred_qualifications": "5、 具备下述条件优先:;c) 熟悉TensorRT、MLIR并跟踪行业技术趋势(Experience on TensorRT or MLIR is highly preferred)",
"job_highlights": "未披露"
},
"contact": {
"recruiter_name": "未披露",
"contact_methods": [
{
"type": "apply_link",
"value": "https://recruitment.t-head.cn/off-campus/position-detail?positionId=739822"
}
]
},
"posting": {
"posting_id": "739822",
"post_date": "2026-09-04",
"hire_time": "未披露",
"update_date": "20260917",
"job_url": "https://recruitment.t-head.cn/off-campus/position-detail?positionId=739822"
},
"fulltext": "平头哥-深度学习推理引擎研发专家-杭州\n平头哥-深度学习推理引擎研发专家-杭州\n\n基础信息\n职位类别:技术-芯片\n工作地点:杭州\n\n职位描述\n1、参与设计和实现推理引擎SDK,提升推理性能、易用性和产品稳定性。(Design and develop inference engine。Focusing on performance、usability and product robustness)\n2、参与设计和实现推理引擎的AI编译。包括图融合、各类图优化、算子优化以及自动化调优等(Design and develop AI Compiling。including fusion,graph optimizations、kernel optimization and auto-tuning)\n3、参与设计和实现推理引擎的运行时系统。包括内存管理以及资源管理等等。实现高效和稳定的稳定性。(Design and develop runtime system,including memory management and resource management)\n4、参与设计和实现大模型的推理优化。基于推理引擎,研发和应用大模型推理优化的技术(Design and optimize LLM inference。Based on inference engine,develop and apply core technology for LLM inference)\n\n职位要求\n1、 CS/EE相关领域,5+年工作经验(A Masters or higher degree in Computer Engineering, Computer Science, Applied Mathematics or related computing focused degree (or equivalent experience), 5+ years of relevant software development experience)\n2、 熟悉C/C++编程(Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design).\n3、 熟悉深度学习框架,如Tensorflow,Pytorch(Familiar with deep learning framework,tensorflow or pytorch etc)\n4、 有较强的技术热情,自我驱动(Proactive and able to work without supervision)\n5、 具备下述条件优先:\na)有AI编译或推理引擎相关研发经验。(Related experience on deep learning compiling or inference engine)\nb) 熟悉CPU/AI架构并有深度学习系统研发经验(Prior experience with performance modelling, profiling, and code optimization in DL)\nc) 熟悉TensorRT、MLIR并跟踪行业技术趋势(Experience on TensorRT or MLIR is highly preferred)\n1、参与设计和实现推理引擎SDK,提升推理性能、易用性和产品稳定性。(Design and develop inference engine。Focusing on performance、usability and product robustness)\n2、参与设计和实现推理引擎的AI编译。包括图融合、各类图优化、算子优化以及自动化调优等(Design and develop AI Compiling。including fusion,graph optimizations、kernel optimization and auto-tuning)\n3、参与设计和实现推理引擎的运行时系统。包括内存管理以及资源管理等等。实现高效和稳定的稳定性。(Design and develop runtime system,including memory management and resource management)\n4、参与设计和实现大模型的推理优化。基于推理引擎,研发和应用大模型推理优化的技术(Design and optimize LLM inference。Based on inference engine,develop and apply core technology for LLM inference)\n1、 CS/EE相关领域,5+年工作经验(A Masters or higher degree in Computer Engineering, Computer Science, Applied Mathematics or related computing focused degree (or equivalent experience), 5+ years of relevant software development experience)\n2、 熟悉C/C++编程(Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design).\n3、 熟悉深度学习框架,如Tensorflow,Pytorch(Familiar with deep learning framework,tensorflow or pytorch etc)\n4、 有较强的技术热情,自我驱动(Proactive and able to work without supervision)\n5、 具备下述条件优先:\na)有AI编译或推理引擎相关研发经验。(Related experience on deep learning compiling or inference engine)\nb) 熟悉CPU/AI架构并有深度学习系统研发经验(Prior experience with performance modelling, profiling, and code optimization in DL)\nc) 熟悉TensorRT、MLIR并跟踪行业技术趋势(Experience on TensorRT or MLIR is highly preferred)",
"standard_classification": {
"std_category_code": "T014",
"std_aux_codes": [],
"std_category_status": null,
"std_taxonomy_version": "20261104"
}
}