{
    "schema_version": "via_ai_product_manager_jobs_v1",
    "data_type": "ai_product_manager_jobs",
    "job": {
        "job_title": "股票激励|大模型分布式训练+框架开发",
        "job_level": "高级",AI生成
        "work_category": "全职",AI生成
        "department": "",
        "location": "香港",
        "work_mode": "现场办公",AI生成
        "job_category": "AI平台基础设施研发工程师"AI生成
    },
    "company": {
        "company_name": "某大型人工智能数据智能上市公司",
        "company_industry": "互联网",
        "company_size": "1000-9999人",
        "company_website": "",
        "company_description": ""
    },
    "compensation": {
        "salary_range": {
            "min": 100000,
            "max": 110000,
            "currency": "CNY",
            "cycle": "month"
        },
        "benefits": ""
    },
    "requirements": {
        "working_years": 3,
        "degree": "本科",
        "language": "中英双语",AI生成
        "visa_support": "",
        "responsibilities": "",
        "requirements_text": "职位要求\n基本要求\n1. 编程能力扎实，有清晰的系统设计思路，有强烈的工程品味和责任心；\n2. 对 AI 训练系统或 RL 工程某⼀⽅向有深⼊理解，能独立发现问题、提出方案并推动落地；\n3. 主动追踪算法与系统前沿，能将论⽂洞见转化为工程判断；\n加分项：\n1. 对主流开源框架（PyTorch、Megatron-LM、SGLang 等）有深入了解，并有实质性贡献\n2. 有万卡规模训练系统或大规模 RLHF/RLVR 工程的实战经验\n认证资质\n人力资源服务许可证",
        "skills": [AI生成
            "编程与代码实现",
            "分布式/微服务系统设计",
            "模型训练与算法优化",
            "Linux/DevOps/CI-CD",
            "技术可行性与系统架构"
        ],
        "preferred_qualifications": "",
        "job_highlights": ""
    },
    "contact": {
        "recruiter_name": "",
        "contact_methods": [
            {
                "type": "apply_link",
                "value": "https://www.zhipin.com/job_detail/2cb81a646d201c700nBz2tq6E1NT.html"
            }
        ]
    },
    "posting": {
        "posting_id": "2cb81a646d201c700nBz2tq6E1NT",
        "post_date": "",
        "hire_time": "",
        "update_date": "",
        "job_url": "https://www.zhipin.com/job_detail/2cb81a646d201c700nBz2tq6E1NT.html"
    },
    "fulltext": "职位要求\n基本要求\n1. 编程能力扎实，有清晰的系统设计思路，有强烈的工程品味和责任心；\n2. 对 AI 训练系统或 RL 工程某⼀⽅向有深⼊理解，能独立发现问题、提出方案并推动落地；\n3. 主动追踪算法与系统前沿，能将论⽂洞见转化为工程判断；\n加分项：\n1. 对主流开源框架（PyTorch、Megatron-LM、SGLang 等）有深入了解，并有实质性贡献\n2. 有万卡规模训练系统或大规模 RLHF/RLVR 工程的实战经验\n认证资质\n人力资源服务许可证"
}