{
    "schema_version": "via_ai_product_manager_jobs_v1",
    "data_type": "ai_product_manager_jobs",
    "job": {
        "job_title": "Kimi Post-Training Algorithm Researcher/Engineer (Code)",
        "job_level": "",AI生成
        "work_category": "全职",AI生成
        "department": "",
        "location": "",
        "work_mode": "",AI生成
        "job_category": "算法类/AI"AI生成
    },
    "company": {
        "company_name": "月之暗面",
        "company_industry": "",
        "company_size": "",
        "company_website": "",
        "company_description": ""
    },
    "compensation": {
        "salary_range": {
            "min": "",
            "max": "",
            "currency": "",
            "cycle": ""
        },
        "benefits": ""
    },
    "requirements": {
        "working_years": "",
        "degree": "",
        "language": "",AI生成
        "visa_support": "",
        "responsibilities": "Job Description:1. Deeply participate in data processing, cleaning, and optimization for CodeLLM; scientifically improve, filter, and balance the data quality used in LLM pre-training and alignment to enhance the model’s code and agent capabilities during the Pretrain and SFT stages.2. Actively engage in improving Coding/SWE Agent capabilities through SFT (Supervised Fine-Tuning), RL (Reinforcement Learning), and building/scaling tools, Docker environments, and tasks; personally gain know-how on how to effectively train an agentic model.3. Deeply explore methods to enhance the model’s problem-solving ability, aiming for: 1) Nearly 100% accuracy on simple and medium-level algorithm problems; 2) Maximizing the solving rate of difficult algorithm problems (IOI/ICPC level), pushing the model’s intelligence upper bound.4. Improve user problem-solving rates and satisfaction on Code/SWE-related questions, making the model genuinely easy and pleasant to use.Job Requirements:1. Bachelor’s degree or above, preferably in Computer Science, Artificial Intelligence, Automation, Mathematics, or related fields.2. Solid programming foundation, deep understanding of data structures and algorithm design; proficient in one or more mainstream programming languages such as Python and C++; skilled in deep learning frameworks and libraries like PyTorch, TensorFlow, and Hugging Face.3. Rich hands-on experience in large model pre-training and alignment training, or experience in Code/SWE optimization is preferred.4. Publication in top-tier academic conferences or outstanding achievements in machine learning and AI fields are preferred.5. Algorithm competition award experience (e.g., ACM, IOI, NOI, Top Coder) is a plus.6. Strong sense of responsibility, proactive attitude, and good communication and teamwork skills.",
        "requirements_text": "",
        "skills": [],AI生成
        "preferred_qualifications": "",
        "job_highlights": ""
    },
    "contact": {
        "recruiter_name": "",
        "contact_methods": []
    },
    "posting": {
        "posting_id": "8bcd1241-2e42-4f70-8b9c-3ab197119d61",
        "post_date": "2025-12-23",
        "hire_time": "",
        "update_date": "",
        "job_url": "https://app.mokahr.com/campus-recruitment/moonshot/148507#/job/8bcd1241-2e42-4f70-8b9c-3ab197119d61"
    },
    "fulltext": "Job Description:1. Deeply participate in data processing, cleaning, and optimization for CodeLLM; scientifically improve, filter, and balance the data quality used in LLM pre-training and alignment to enhance the model’s code and agent capabilities during the Pretrain and SFT stages.2. Actively engage in improving Coding/SWE Agent capabilities through SFT (Supervised Fine-Tuning), RL (Reinforcement Learning), and building/scaling tools, Docker environments, and tasks; personally gain know-how on how to effectively train an agentic model.3. Deeply explore methods to enhance the model’s problem-solving ability, aiming for: 1) Nearly 100% accuracy on simple and medium-level algorithm problems; 2) Maximizing the solving rate of difficult algorithm problems (IOI/ICPC level), pushing the model’s intelligence upper bound.4. Improve user problem-solving rates and satisfaction on Code/SWE-related questions, making the model genuinely easy and pleasant to use.Job Requirements:1. Bachelor’s degree or above, preferably in Computer Science, Artificial Intelligence, Automation, Mathematics, or related fields.2. Solid programming foundation, deep understanding of data structures and algorithm design; proficient in one or more mainstream programming languages such as Python and C++; skilled in deep learning frameworks and libraries like PyTorch, TensorFlow, and Hugging Face.3. Rich hands-on experience in large model pre-training and alignment training, or experience in Code/SWE optimization is preferred.4. Publication in top-tier academic conferences or outstanding achievements in machine learning and AI fields are preferred.5. Algorithm competition award experience (e.g., ACM, IOI, NOI, Top Coder) is a plus.6. Strong sense of responsibility, proactive attitude, and good communication and teamwork skills."
}