{
    "schema_version": "via_ai_product_manager_jobs_v1",
    "data_type": "ai_product_manager_jobs",
    "job": {
        "job_title": "Hunyuan Multimodal Reinforcement Learning (RL) Research Intern 107383",
        "job_level": "实习",AI生成
        "work_category": "实习",AI生成
        "department": "TEG",
        "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\nTechnology Engineering Group (TEG) is responsible for supporting the company and its business groups on technology and operational platforms, as well as the construction and operation of R&D management and data centers, TEG provides users with a full range of customer services. As the operator of the largest networking, devices, and data center in Asia,TEG also leads the Tencent Technology Committee in strengthening infrastructure R&D through internal and distributed open source collaboration, constructing new platforms and supporting business innovation.\n\nWhat the Role Entails\n1. Conduct research on RL algorithms for multimodal models, including diffusion models for image, video, and 3D generation, autoregressive models for multimodal understanding, and potentially unified multimodal frameworks.\n2. Design and develop RL infrastructure and reward modeling strategies to enable efficient large-scale training, improve training stability, and mitigate reward hacking and related failure modes.\n3. Explore next-generation RL paradigms that more directly and effectively learn from environment feedback.\n\nWho We Look For\n1. Currently enrolled as a PhD student in Computer Science or a closely related field.\n2. Demonstrated strong research capability, with publications in top-tier conferences such as ICML, NeurIPS, ICLR, CVPR, ICCV, ECCV, SIGGRAPH.\n3. Strong hands-on programming skills, with solid experience in deep learning system implementation, model training and inference optimization, CPU/GPU acceleration, and distributed training and inference.\n4. Prior experience with diffusion models, autoregressive models, and/or text-to-image or text-to-video generation is highly preferred.\n5. Participation in ACM/NOIP is a strong plus.\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
            "深度学习",
            "团队协作"
        ],
        "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/Hunyuan-Multimodal-Reinforcement-Learning--RL--Research-Intern_R107383"
            }
        ]
    },
    "posting": {
        "posting_id": "2047515918577336320",
        "post_date": "2026-04-23",
        "hire_time": "未披露",
        "update_date": "20260917",
        "job_url": "https://tencent.wd1.myworkdayjobs.com/Tencent_Careers/job/Singapore-CapitaSky/Hunyuan-Multimodal-Reinforcement-Learning--RL--Research-Intern_R107383"
    },
    "fulltext": "Hunyuan Multimodal Reinforcement Learning (RL) Research Intern 107383\nBusiness Unit\nTechnology Engineering Group (TEG) is responsible for supporting the company and its business groups on technology and operational platforms, as well as the construction and operation of R&D management and data centers, TEG provides users with a full range of customer services. As the operator of the largest networking, devices, and data center in Asia,TEG also leads the Tencent Technology Committee in strengthening infrastructure R&D through internal and distributed open source collaboration, constructing new platforms and supporting business innovation.\n\nWhat the Role Entails\n1. Conduct research on RL algorithms for multimodal models, including diffusion models for image, video, and 3D generation, autoregressive models for multimodal understanding, and potentially unified multimodal frameworks.\n2. Design and develop RL infrastructure and reward modeling strategies to enable efficient large-scale training, improve training stability, and mitigate reward hacking and related failure modes.\n3. Explore next-generation RL paradigms that more directly and effectively learn from environment feedback.\n\nWho We Look For\n1. Currently enrolled as a PhD student in Computer Science or a closely related field.\n2. Demonstrated strong research capability, with publications in top-tier conferences such as ICML, NeurIPS, ICLR, CVPR, ICCV, ECCV, SIGGRAPH.\n3. Strong hands-on programming skills, with solid experience in deep learning system implementation, model training and inference optimization, CPU/GPU acceleration, and distributed training and inference.\n4. Prior experience with diffusion models, autoregressive models, and/or text-to-image or text-to-video generation is highly preferred.\n5. Participation in ACM/NOIP is a strong plus.\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": "T010",
        "std_aux_codes": [],
        "std_category_status": null,
        "std_taxonomy_version": "20261104"
    }
}