混元平台产品策划（深圳/北京）
Tencent
混元平台产品策划（深圳/北京）
Job Description
混元平台产品策划（深圳/北京）
📋 Job Overview
The Product Planner for the Tai Chi Hunyuan Base Model Platform will lead the full-cycle product planning, focusing on data processing, model training, and performance evaluation to enhance platform efficiency. The role involves building optimization systems for training and deployment, collaborating with cross-functional teams to ensure timely delivery, and driving iterative improvements based on feedback and industry trends. This position is based in Shenzhen or Beijing and aims to scale base model training from 1 to N.
📍 Location: Shenzhen, China
🏢 Business Unit: TEG
📄 Full Description
1.负责太极混元基模平台全流程产品规划：聚焦平台内基模的数据处理、模型训练、性能评估等核心环节，精准定位算法选型、训练框架适配等技术痛点，主导产品方案设计，推动基模从1到N的规模化训练落地，核心目标为提升平台研发效率；
2.构建基模训练部署评估效能优化体系，针对训练评估过程中痛点，设计并落地方案，全面提升基模训练的效率、稳定性与可追溯性；
3.联动多技术团队推进平台落地：协同算法团队、工程团队（框架,算力，调度）、数据团队等，对齐跨团队需求与目标，解决研发过程中的协作问题，保障平台功能及基模训练任务按时高质量交付；
4.驱动平台迭代与体验优化：收集平台内算法、研发团队的使用反馈，结合基模训练技术趋势（如分布式训练、低资源训练等），制定平台迭代 roadmap，持续优化产品功能，强化太极混元平台在基模训练场景的核心竞争力。
2.构建基模训练部署评估效能优化体系，针对训练评估过程中痛点，设计并落地方案，全面提升基模训练的效率、稳定性与可追溯性；
3.联动多技术团队推进平台落地：协同算法团队、工程团队（框架,算力，调度）、数据团队等，对齐跨团队需求与目标，解决研发过程中的协作问题，保障平台功能及基模训练任务按时高质量交付；
4.驱动平台迭代与体验优化：收集平台内算法、研发团队的使用反馈，结合基模训练技术趋势（如分布式训练、低资源训练等），制定平台迭代 roadmap，持续优化产品功能，强化太极混元平台在基模训练场景的核心竞争力。
🎯 Key Responsibilities
- Responsible for the full process product planning of the Tai Chi Hunyuan base model platform: focusing on core links such as data processing, model training, and performance evaluation within the platform, accurately identifying technical pain points like algorithm selection and training framework adaptation, leading product solution design, promoting the scalable training implementation of base models from 1 to N, with the core goal of improving platform R&D efficiency.
- Build an optimization system for base model training, deployment, and evaluation efficiency, design and implement solutions for pain points in the training and evaluation process, comprehensively enhancing the efficiency, stability, and traceability of base model training.
- Collaborate with multiple technical teams to advance platform implementation: coordinate with algorithm teams, engineering teams (framework, computing power, scheduling), data teams, etc., align cross-team needs and goals, resolve collaboration issues in the R&D process, and ensure high-quality on-time delivery of platform functions and base model training tasks.
- Drive platform iteration and experience optimization: collect usage feedback from algorithm and R&D teams within the platform, combined with base model training technology trends (such as distributed training, low-resource training, etc.), formulate platform iteration roadmap, continuously optimize product functions, and strengthen the core competitiveness of the Tai Chi Hunyuan platform in base model training scenarios.
Locations
- Shenzhen, China
Salary
Estimated Salary Rangemedium confidence
300,000 - 600,000 CNY / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Responsibilities
- Responsible for the full process product planning of the Tai Chi Hunyuan base model platform: focusing on core links such as data processing, model training, and performance evaluation within the platform, accurately identifying technical pain points like algorithm selection and training framework adaptation, leading product solution design, promoting the scalable training implementation of base models from 1 to N, with the core goal of improving platform R&D efficiency.
- Build an optimization system for base model training, deployment, and evaluation efficiency, design and implement solutions for pain points in the training and evaluation process, comprehensively enhancing the efficiency, stability, and traceability of base model training.
- Collaborate with multiple technical teams to advance platform implementation: coordinate with algorithm teams, engineering teams (framework, computing power, scheduling), data teams, etc., align cross-team needs and goals, resolve collaboration issues in the R&D process, and ensure high-quality on-time delivery of platform functions and base model training tasks.
- Drive platform iteration and experience optimization: collect usage feedback from algorithm and R&D teams within the platform, combined with base model training technology trends (such as distributed training, low-resource training, etc.), formulate platform iteration roadmap, continuously optimize product functions, and strengthen the core competitiveness of the Tai Chi Hunyuan platform in base model training scenarios.
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混元平台产品策划（深圳/北京）
Tencent
混元平台产品策划（深圳/北京）
Job Description
混元平台产品策划（深圳/北京）
📋 Job Overview
The Product Planner for the Tai Chi Hunyuan Base Model Platform will lead the full-cycle product planning, focusing on data processing, model training, and performance evaluation to enhance platform efficiency. The role involves building optimization systems for training and deployment, collaborating with cross-functional teams to ensure timely delivery, and driving iterative improvements based on feedback and industry trends. This position is based in Shenzhen or Beijing and aims to scale base model training from 1 to N.
📍 Location: Shenzhen, China
🏢 Business Unit: TEG
📄 Full Description
1.负责太极混元基模平台全流程产品规划：聚焦平台内基模的数据处理、模型训练、性能评估等核心环节，精准定位算法选型、训练框架适配等技术痛点，主导产品方案设计，推动基模从1到N的规模化训练落地，核心目标为提升平台研发效率；
2.构建基模训练部署评估效能优化体系，针对训练评估过程中痛点，设计并落地方案，全面提升基模训练的效率、稳定性与可追溯性；
3.联动多技术团队推进平台落地：协同算法团队、工程团队（框架,算力，调度）、数据团队等，对齐跨团队需求与目标，解决研发过程中的协作问题，保障平台功能及基模训练任务按时高质量交付；
4.驱动平台迭代与体验优化：收集平台内算法、研发团队的使用反馈，结合基模训练技术趋势（如分布式训练、低资源训练等），制定平台迭代 roadmap，持续优化产品功能，强化太极混元平台在基模训练场景的核心竞争力。
2.构建基模训练部署评估效能优化体系，针对训练评估过程中痛点，设计并落地方案，全面提升基模训练的效率、稳定性与可追溯性；
3.联动多技术团队推进平台落地：协同算法团队、工程团队（框架,算力，调度）、数据团队等，对齐跨团队需求与目标，解决研发过程中的协作问题，保障平台功能及基模训练任务按时高质量交付；
4.驱动平台迭代与体验优化：收集平台内算法、研发团队的使用反馈，结合基模训练技术趋势（如分布式训练、低资源训练等），制定平台迭代 roadmap，持续优化产品功能，强化太极混元平台在基模训练场景的核心竞争力。
🎯 Key Responsibilities
- Responsible for the full process product planning of the Tai Chi Hunyuan base model platform: focusing on core links such as data processing, model training, and performance evaluation within the platform, accurately identifying technical pain points like algorithm selection and training framework adaptation, leading product solution design, promoting the scalable training implementation of base models from 1 to N, with the core goal of improving platform R&D efficiency.
- Build an optimization system for base model training, deployment, and evaluation efficiency, design and implement solutions for pain points in the training and evaluation process, comprehensively enhancing the efficiency, stability, and traceability of base model training.
- Collaborate with multiple technical teams to advance platform implementation: coordinate with algorithm teams, engineering teams (framework, computing power, scheduling), data teams, etc., align cross-team needs and goals, resolve collaboration issues in the R&D process, and ensure high-quality on-time delivery of platform functions and base model training tasks.
- Drive platform iteration and experience optimization: collect usage feedback from algorithm and R&D teams within the platform, combined with base model training technology trends (such as distributed training, low-resource training, etc.), formulate platform iteration roadmap, continuously optimize product functions, and strengthen the core competitiveness of the Tai Chi Hunyuan platform in base model training scenarios.
Locations
- Shenzhen, China
Salary
Estimated Salary Rangemedium confidence
300,000 - 600,000 CNY / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Responsibilities
- Responsible for the full process product planning of the Tai Chi Hunyuan base model platform: focusing on core links such as data processing, model training, and performance evaluation within the platform, accurately identifying technical pain points like algorithm selection and training framework adaptation, leading product solution design, promoting the scalable training implementation of base models from 1 to N, with the core goal of improving platform R&D efficiency.
- Build an optimization system for base model training, deployment, and evaluation efficiency, design and implement solutions for pain points in the training and evaluation process, comprehensively enhancing the efficiency, stability, and traceability of base model training.
- Collaborate with multiple technical teams to advance platform implementation: coordinate with algorithm teams, engineering teams (framework, computing power, scheduling), data teams, etc., align cross-team needs and goals, resolve collaboration issues in the R&D process, and ensure high-quality on-time delivery of platform functions and base model training tasks.
- Drive platform iteration and experience optimization: collect usage feedback from algorithm and R&D teams within the platform, combined with base model training technology trends (such as distributed training, low-resource training, etc.), formulate platform iteration roadmap, continuously optimize product functions, and strengthen the core competitiveness of the Tai Chi Hunyuan platform in base model training scenarios.
Tags & Categories
Answer 10 quick questions to check your fit for 混元平台产品策划（深圳/北京） @ Tencent.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs