腾讯智能座舱-多模态大模型数据专家
Tencent
腾讯智能座舱-多模态大模型数据专家
Job Description
腾讯智能座舱-多模态大模型数据专家
📋 Job Overview
The role focuses on building and optimizing automated data processing pipelines for multimodal large models in intelligent cockpit scenarios, covering data acquisition, cleaning, synthesis, quality assessment, and version management. Responsibilities include developing tools for efficient data handling, establishing quality evaluation systems to identify and resolve data issues, and collaborating with algorithm teams to customize data strategies that drive model performance improvements. This position supports continuous iteration of models through data-driven optimization in a dynamic business environment.
📍 Location: Shenzhen, China
🏢 Business Unit: CSIG
📄 Full Description
2.开发自动化数据处理工具与脚本，优化数据清洗、标注及合成的效率和规模化能力；
3.建立数据质量评估指标体系与自动化检测机制，通过数据实验分析识别样本不足、质量问题、配比不均衡等潜在问题，驱动数据优化并量化数据对模型效果的提升；
4.与算法团队深度协作，理解模型训练需求与业务场景特性，定制数据策略，分析挖掘数据资源，支持模型持续迭代，推动数据驱动的模型性能优化。
🎯 Key Responsibilities
- Build automated, high-efficiency data processing pipelines for pre-training and post-training data needs of multimodal large models in intelligent cockpit scenarios, including data crawling, cleaning, synthesis, quality assessment, and version management; optimize component performance to ensure stability and scalability.
- Develop automated data processing tools and scripts to optimize the efficiency and scalability of data cleaning, annotation, and synthesis.
- Establish a data quality assessment indicator system and automated detection mechanisms; analyze data experiments to identify issues such as sample deficiencies, quality problems, and imbalance in ratios; drive data optimization and quantify the impact of data on model performance improvements.
- Collaborate deeply with algorithm teams to understand model training needs and business scenario characteristics; customize data strategies, analyze and mine data resources to support continuous model iteration and promote data-driven model performance optimization.
Locations
- Shenzhen, China
Salary
300,000 - 800,000 CNY / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Responsibilities
- Build automated, high-efficiency data processing pipelines for pre-training and post-training data needs of multimodal large models in intelligent cockpit scenarios, including data crawling, cleaning, synthesis, quality assessment, and version management; optimize component performance to ensure stability and scalability.
- Develop automated data processing tools and scripts to optimize the efficiency and scalability of data cleaning, annotation, and synthesis.
- Establish a data quality assessment indicator system and automated detection mechanisms; analyze data experiments to identify issues such as sample deficiencies, quality problems, and imbalance in ratios; drive data optimization and quantify the impact of data on model performance improvements.
- Collaborate deeply with algorithm teams to understand model training needs and business scenario characteristics; customize data strategies, analyze and mine data resources to support continuous model iteration and promote data-driven model performance optimization.
Tags & Categories
Answer 10 quick questions to check your fit for 腾讯智能座舱-多模态大模型数据专家 @ Tencent.
Related Books and Jobs
腾讯智能座舱-多模态大模型数据专家
Tencent
腾讯智能座舱-多模态大模型数据专家
Job Description
腾讯智能座舱-多模态大模型数据专家
📋 Job Overview
The role focuses on building and optimizing automated data processing pipelines for multimodal large models in intelligent cockpit scenarios, covering data acquisition, cleaning, synthesis, quality assessment, and version management. Responsibilities include developing tools for efficient data handling, establishing quality evaluation systems to identify and resolve data issues, and collaborating with algorithm teams to customize data strategies that drive model performance improvements. This position supports continuous iteration of models through data-driven optimization in a dynamic business environment.
📍 Location: Shenzhen, China
🏢 Business Unit: CSIG
📄 Full Description
2.开发自动化数据处理工具与脚本，优化数据清洗、标注及合成的效率和规模化能力；
3.建立数据质量评估指标体系与自动化检测机制，通过数据实验分析识别样本不足、质量问题、配比不均衡等潜在问题，驱动数据优化并量化数据对模型效果的提升；
4.与算法团队深度协作，理解模型训练需求与业务场景特性，定制数据策略，分析挖掘数据资源，支持模型持续迭代，推动数据驱动的模型性能优化。
🎯 Key Responsibilities
- Build automated, high-efficiency data processing pipelines for pre-training and post-training data needs of multimodal large models in intelligent cockpit scenarios, including data crawling, cleaning, synthesis, quality assessment, and version management; optimize component performance to ensure stability and scalability.
- Develop automated data processing tools and scripts to optimize the efficiency and scalability of data cleaning, annotation, and synthesis.
- Establish a data quality assessment indicator system and automated detection mechanisms; analyze data experiments to identify issues such as sample deficiencies, quality problems, and imbalance in ratios; drive data optimization and quantify the impact of data on model performance improvements.
- Collaborate deeply with algorithm teams to understand model training needs and business scenario characteristics; customize data strategies, analyze and mine data resources to support continuous model iteration and promote data-driven model performance optimization.
Locations
- Shenzhen, China
Salary
300,000 - 800,000 CNY / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Responsibilities
- Build automated, high-efficiency data processing pipelines for pre-training and post-training data needs of multimodal large models in intelligent cockpit scenarios, including data crawling, cleaning, synthesis, quality assessment, and version management; optimize component performance to ensure stability and scalability.
- Develop automated data processing tools and scripts to optimize the efficiency and scalability of data cleaning, annotation, and synthesis.
- Establish a data quality assessment indicator system and automated detection mechanisms; analyze data experiments to identify issues such as sample deficiencies, quality problems, and imbalance in ratios; drive data optimization and quantify the impact of data on model performance improvements.
- Collaborate deeply with algorithm teams to understand model training needs and business scenario characteristics; customize data strategies, analyze and mine data resources to support continuous model iteration and promote data-driven model performance optimization.
Tags & Categories
Answer 10 quick questions to check your fit for 腾讯智能座舱-多模态大模型数据专家 @ Tencent.
Related Books and Jobs