{
    "schema_version": "via_ai_product_manager_jobs_v1",
    "data_type": "ai_product_manager_jobs",
    "job": {
        "job_title": "Cloud Engineer Intern 107771",
        "job_level": "实习",AI生成
        "work_category": "实习",AI生成
        "department": "WXG",
        "location": "新加坡",
        "work_mode": "未披露",AI生成
        "job_category": "技术"AI生成
    },
    "company": {
        "company_name": "腾讯",
        "company_industry": "互联网 / 科技 / 人工智能",
        "company_size": "10000人以上",
        "company_website": "tencent.com",
        "company_description": "腾讯是一家互联网和科技公司，业务覆盖通信与社交、数字内容、游戏、金融科技、企业服务、云计算与人工智能等方向。"
    },
    "compensation": {
        "salary_range": {
            "min": "",
            "max": "",
            "currency": "未披露",
            "cycle": "未披露"
        },
        "benefits": "未披露"
    },
    "requirements": {
        "working_years": "",
        "degree": "未披露",
        "language": "未披露",AI生成
        "visa_support": "未披露",
        "responsibilities": "Business Unit\nWeiXin Group(WXG) is responsible for the construction and operation of the Weixin ecosystem and leveraging Weixin's open platforms such as Official Accounts, Mini Programs, Weixin Pay, WeCom and search function. WXG provides solutions and connectivity for intelligent upgrades across all industries. WXG is also responsible for the development and operation of QQ Mail, WeRead and other products.\n\nWhat the Role Entails\nYou will support the reliability, scalability, and security of Tencent’s business-critical systems in a cloud-native environment: \nSystem Monitoring & Incident Response Monitor production systems using tools like Prometheus/Grafana; identify and troubleshoot outages. \nParticipate in on-call rotations to resolve real-time incidents (with mentor guidance). \n\nAutomation & DevOps Practices Develop scripts (Python/Shell) to automate deployment, scaling, and recovery tasks. \nAssist in CI/CD pipeline optimization using GitLab, Docker, and Kubernetes. \n\nInfrastructure Optimization Analyze system performance metrics; propose solutions to enhance reliability and cost efficiency. \nSupport cloud infrastructure management (Tencent Cloud/AWS/Azure). \n\nCollaboration & DocumentationWork with cross-functional teams (Dev, Data, Security) to design SLOs/SLIs for critical services.\nDocument system configurations, runbooks, and post-incident reports.\n\nWho We Look For\nEducation & BackgroundCurrently pursuing an undergraduate or graduate degree in Computer Science, AI, Machine Learning, or a related fields.\nStrong foundation in deep learning and machine learning fundamentals.\nTechnical SkillsProgramming: Proficient in Python and PyTorch / JAX\nScripting: Python, Shell, or Go\nOS: Linux / Unix system administration\nNetworking: TCP/IP, DNS, HTTP basics\nCloud Platforms: Experience with Tencent Cloud, AWS, or Azure\nIaC & Observability: Familiarity with tools such as Terraform, Ansible, ELK, or Prometheus\nContainerization: Knowledge of Docker / Kubernetes\n\nCore CompetenciesStrong analytical and problem-solving mindset, with a passion for infrastructure technologies.\nAbility to learn quickly and thrive in a fast-paced environment.\nPublications at top conferences (CVPR, ICCV, NeurIPS, ICLR, ACL, etc.) .\nExperience training large models or working with distributed systems.\nExperience with multimodal datasets and evaluation benchmarks.\nRequire bilingual proficiency as 80% of communications with global and HQ teams are conducted in both English and Mandarin.\nMust-Have ExperienceAt least one of the following areas:\nVision-language models (VLMs)\nLarge language models (LLMs)\nVideo understanding and generation\nReinforcement learning or imitation learning\nTransformer architectures and scaling laws\nMultimodal alignment (contrastive learning, instruction tuning)\nAgent training (RLHF/RLAIF, planning, tool use)\nSynthetic data generation or simulation environments\nExperience with long-context training or memory mechanisms\n\nEqual Employment Opportunity at Tencent\nAs an equal opportunity employer, we firmly believe that diverse voices fuel our innovation and allow us to better serve our users and the community. We foster an environment where every employee of Tencent feels supported and inspired to achieve individual and common goals.\r\nWork Location: Singapore-CapitaSky",
        "requirements_text": "岗位要求详情请见上方岗位职责内说明",
        "skills": [AI生成
            "Python",
            "Linux",
            "Docker",
            "Kubernetes",
            "PyTorch",
            "机器学习",
            "深度学习",
            "团队协作",
            "Go",
            "大语言模型"
        ],
        "preferred_qualifications": "未披露",
        "job_highlights": "未披露"
    },
    "contact": {
        "recruiter_name": "未披露",
        "contact_methods": [
            {
                "type": "apply_link",
                "value": "https://tencent.wd1.myworkdayjobs.com/Tencent_Careers/job/Singapore-CapitaSky/Cloud-Engineer-Intern_R107771"
            }
        ]
    },
    "posting": {
        "posting_id": "2075480224212107264",
        "post_date": "2026-08-17",
        "hire_time": "未披露",
        "update_date": "20260917",
        "job_url": "https://tencent.wd1.myworkdayjobs.com/Tencent_Careers/job/Singapore-CapitaSky/Cloud-Engineer-Intern_R107771"
    },
    "fulltext": "Cloud Engineer Intern 107771\nBusiness Unit\nWeiXin Group(WXG) is responsible for the construction and operation of the Weixin ecosystem and leveraging Weixin's open platforms such as Official Accounts, Mini Programs, Weixin Pay, WeCom and search function. WXG provides solutions and connectivity for intelligent upgrades across all industries. WXG is also responsible for the development and operation of QQ Mail, WeRead and other products.\n\nWhat the Role Entails\nYou will support the reliability, scalability, and security of Tencent’s business-critical systems in a cloud-native environment: \nSystem Monitoring & Incident Response Monitor production systems using tools like Prometheus/Grafana; identify and troubleshoot outages. \nParticipate in on-call rotations to resolve real-time incidents (with mentor guidance). \n\nAutomation & DevOps Practices Develop scripts (Python/Shell) to automate deployment, scaling, and recovery tasks. \nAssist in CI/CD pipeline optimization using GitLab, Docker, and Kubernetes. \n\nInfrastructure Optimization Analyze system performance metrics; propose solutions to enhance reliability and cost efficiency. \nSupport cloud infrastructure management (Tencent Cloud/AWS/Azure). \n\nCollaboration & DocumentationWork with cross-functional teams (Dev, Data, Security) to design SLOs/SLIs for critical services.\nDocument system configurations, runbooks, and post-incident reports.\n\nWho We Look For\nEducation & BackgroundCurrently pursuing an undergraduate or graduate degree in Computer Science, AI, Machine Learning, or a related fields.\nStrong foundation in deep learning and machine learning fundamentals.\nTechnical SkillsProgramming: Proficient in Python and PyTorch / JAX\nScripting: Python, Shell, or Go\nOS: Linux / Unix system administration\nNetworking: TCP/IP, DNS, HTTP basics\nCloud Platforms: Experience with Tencent Cloud, AWS, or Azure\nIaC & Observability: Familiarity with tools such as Terraform, Ansible, ELK, or Prometheus\nContainerization: Knowledge of Docker / Kubernetes\n\nCore CompetenciesStrong analytical and problem-solving mindset, with a passion for infrastructure technologies.\nAbility to learn quickly and thrive in a fast-paced environment.\nPublications at top conferences (CVPR, ICCV, NeurIPS, ICLR, ACL, etc.) .\nExperience training large models or working with distributed systems.\nExperience with multimodal datasets and evaluation benchmarks.\nRequire bilingual proficiency as 80% of communications with global and HQ teams are conducted in both English and Mandarin.\nMust-Have ExperienceAt least one of the following areas:\nVision-language models (VLMs)\nLarge language models (LLMs)\nVideo understanding and generation\nReinforcement learning or imitation learning\nTransformer architectures and scaling laws\nMultimodal alignment (contrastive learning, instruction tuning)\nAgent training (RLHF/RLAIF, planning, tool use)\nSynthetic data generation or simulation environments\nExperience with long-context training or memory mechanisms\n\nEqual Employment Opportunity at Tencent\nAs an equal opportunity employer, we firmly believe that diverse voices fuel our innovation and allow us to better serve our users and the community. We foster an environment where every employee of Tencent feels supported and inspired to achieve individual and common goals.\r\nWork Location: Singapore-CapitaSky\n岗位要求详情请见上方岗位职责内说明",
    "standard_classification": {
        "std_category_code": "T020",
        "std_aux_codes": [],
        "std_category_status": null,
        "std_taxonomy_version": "20261104"
    }
}