混元大模型标注算法研究员（北京）
Tencent
混元大模型标注算法研究员（北京）
Job Description
混元大模型标注算法研究员（北京）
📋 Job Overview
The role of Mixed Yuan Large Model Annotation Algorithm Researcher in Beijing involves collaborating with data annotation, algorithm development, and product teams to provide technical support for data labeling processes throughout project lifecycles. Key responsibilities include designing and implementing efficient auto/semi-automatic annotation algorithms for text, images, audio, and video data to enhance efficiency and accuracy. The position also focuses on researching advanced machine learning techniques like semi-supervised and active learning, as well as continuously iterating and optimizing annotation models to meet diverse project needs.
📍 Location: Shenzhen, China
🏢 Business Unit: TEG
📄 Full Description
1.与数据标注团队紧密合作，深入了解业务需求，为数据标注工作提供专业的技术支持与指导。与算法研发团队、产品团队等协同工作，参与项目的全生命周期，从需求分析到产品上线，保障数据标注相关算法与功能的顺利实现；
2.针对文本、图像、音频、视频等多类型数据，设计并实现高效的自动 / 半自动标注算法，大幅提升数据标注效率与准确性。2）研究并应用前沿机器学习算法，如半监督学习、主动学习算法，降低数据标注工作量，提升标注数据质量；
3.标注模型持续迭代与优化：对模型进行持续调优，以适应不同项目的数据特点与标注需求，提高模型在数据标注任务上的性能表现。分析、评估模型/工具效果，提出针对性的改进策略，推动标注模型/工具的迭代升级。
2.针对文本、图像、音频、视频等多类型数据，设计并实现高效的自动 / 半自动标注算法，大幅提升数据标注效率与准确性。2）研究并应用前沿机器学习算法，如半监督学习、主动学习算法，降低数据标注工作量，提升标注数据质量；
3.标注模型持续迭代与优化：对模型进行持续调优，以适应不同项目的数据特点与标注需求，提高模型在数据标注任务上的性能表现。分析、评估模型/工具效果，提出针对性的改进策略，推动标注模型/工具的迭代升级。
🎯 Key Responsibilities
- Closely collaborate with the data annotation team to understand business needs and provide professional technical support and guidance for data annotation work.
- Work synergistically with algorithm R&D teams, product teams, etc., participating in the full project lifecycle from requirements analysis to product launch, ensuring the smooth implementation of data annotation-related algorithms and functions.
- For multi-type data such as text, images, audio, and video, design and implement efficient automatic/semi-automatic annotation algorithms to significantly improve data annotation efficiency and accuracy.
- Research and apply cutting-edge machine learning algorithms, such as semi-supervised learning and active learning algorithms, to reduce data annotation workload and enhance annotation data quality.
- Continuously iterate and optimize annotation models: perform ongoing tuning to adapt to different project data characteristics and annotation needs, improving model performance in data annotation tasks.
- Analyze and evaluate the effectiveness of models/tools, propose targeted improvement strategies, and drive the iterative upgrades of annotation models/tools.
🛠️ Required Skills
- Expertise in designing and implementing automatic/semi-automatic annotation algorithms for multi-modal data (text, images, audio, video).
- Knowledge of frontier machine learning algorithms, including semi-supervised learning and active learning.
- Skills in model iteration, optimization, analysis, and evaluation for data annotation tasks.
- Ability to collaborate across teams in full project lifecycle management.
Locations
- Shenzhen, China
Salary
Estimated Salary Rangemedium confidence
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.
Skills Required
- Expertise in designing and implementing automatic/semi-automatic annotation algorithms for multi-modal data (text, images, audio, video).intermediate
- Knowledge of frontier machine learning algorithms, including semi-supervised learning and active learning.intermediate
- Skills in model iteration, optimization, analysis, and evaluation for data annotation tasks.intermediate
- Ability to collaborate across teams in full project lifecycle management.intermediate
Responsibilities
- Closely collaborate with the data annotation team to understand business needs and provide professional technical support and guidance for data annotation work.
- Work synergistically with algorithm R&D teams, product teams, etc., participating in the full project lifecycle from requirements analysis to product launch, ensuring the smooth implementation of data annotation-related algorithms and functions.
- For multi-type data such as text, images, audio, and video, design and implement efficient automatic/semi-automatic annotation algorithms to significantly improve data annotation efficiency and accuracy.
- Research and apply cutting-edge machine learning algorithms, such as semi-supervised learning and active learning algorithms, to reduce data annotation workload and enhance annotation data quality.
- Continuously iterate and optimize annotation models: perform ongoing tuning to adapt to different project data characteristics and annotation needs, improving model performance in data annotation tasks.
- Analyze and evaluate the effectiveness of models/tools, propose targeted improvement strategies, and drive the iterative upgrades of annotation models/tools.
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混元大模型标注算法研究员（北京）
Tencent
混元大模型标注算法研究员（北京）
Job Description
混元大模型标注算法研究员（北京）
📋 Job Overview
The role of Mixed Yuan Large Model Annotation Algorithm Researcher in Beijing involves collaborating with data annotation, algorithm development, and product teams to provide technical support for data labeling processes throughout project lifecycles. Key responsibilities include designing and implementing efficient auto/semi-automatic annotation algorithms for text, images, audio, and video data to enhance efficiency and accuracy. The position also focuses on researching advanced machine learning techniques like semi-supervised and active learning, as well as continuously iterating and optimizing annotation models to meet diverse project needs.
📍 Location: Shenzhen, China
🏢 Business Unit: TEG
📄 Full Description
1.与数据标注团队紧密合作，深入了解业务需求，为数据标注工作提供专业的技术支持与指导。与算法研发团队、产品团队等协同工作，参与项目的全生命周期，从需求分析到产品上线，保障数据标注相关算法与功能的顺利实现；
2.针对文本、图像、音频、视频等多类型数据，设计并实现高效的自动 / 半自动标注算法，大幅提升数据标注效率与准确性。2）研究并应用前沿机器学习算法，如半监督学习、主动学习算法，降低数据标注工作量，提升标注数据质量；
3.标注模型持续迭代与优化：对模型进行持续调优，以适应不同项目的数据特点与标注需求，提高模型在数据标注任务上的性能表现。分析、评估模型/工具效果，提出针对性的改进策略，推动标注模型/工具的迭代升级。
2.针对文本、图像、音频、视频等多类型数据，设计并实现高效的自动 / 半自动标注算法，大幅提升数据标注效率与准确性。2）研究并应用前沿机器学习算法，如半监督学习、主动学习算法，降低数据标注工作量，提升标注数据质量；
3.标注模型持续迭代与优化：对模型进行持续调优，以适应不同项目的数据特点与标注需求，提高模型在数据标注任务上的性能表现。分析、评估模型/工具效果，提出针对性的改进策略，推动标注模型/工具的迭代升级。
🎯 Key Responsibilities
- Closely collaborate with the data annotation team to understand business needs and provide professional technical support and guidance for data annotation work.
- Work synergistically with algorithm R&D teams, product teams, etc., participating in the full project lifecycle from requirements analysis to product launch, ensuring the smooth implementation of data annotation-related algorithms and functions.
- For multi-type data such as text, images, audio, and video, design and implement efficient automatic/semi-automatic annotation algorithms to significantly improve data annotation efficiency and accuracy.
- Research and apply cutting-edge machine learning algorithms, such as semi-supervised learning and active learning algorithms, to reduce data annotation workload and enhance annotation data quality.
- Continuously iterate and optimize annotation models: perform ongoing tuning to adapt to different project data characteristics and annotation needs, improving model performance in data annotation tasks.
- Analyze and evaluate the effectiveness of models/tools, propose targeted improvement strategies, and drive the iterative upgrades of annotation models/tools.
🛠️ Required Skills
- Expertise in designing and implementing automatic/semi-automatic annotation algorithms for multi-modal data (text, images, audio, video).
- Knowledge of frontier machine learning algorithms, including semi-supervised learning and active learning.
- Skills in model iteration, optimization, analysis, and evaluation for data annotation tasks.
- Ability to collaborate across teams in full project lifecycle management.
Locations
- Shenzhen, China
Salary
Estimated Salary Rangemedium confidence
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.
Skills Required
- Expertise in designing and implementing automatic/semi-automatic annotation algorithms for multi-modal data (text, images, audio, video).intermediate
- Knowledge of frontier machine learning algorithms, including semi-supervised learning and active learning.intermediate
- Skills in model iteration, optimization, analysis, and evaluation for data annotation tasks.intermediate
- Ability to collaborate across teams in full project lifecycle management.intermediate
Responsibilities
- Closely collaborate with the data annotation team to understand business needs and provide professional technical support and guidance for data annotation work.
- Work synergistically with algorithm R&D teams, product teams, etc., participating in the full project lifecycle from requirements analysis to product launch, ensuring the smooth implementation of data annotation-related algorithms and functions.
- For multi-type data such as text, images, audio, and video, design and implement efficient automatic/semi-automatic annotation algorithms to significantly improve data annotation efficiency and accuracy.
- Research and apply cutting-edge machine learning algorithms, such as semi-supervised learning and active learning algorithms, to reduce data annotation workload and enhance annotation data quality.
- Continuously iterate and optimize annotation models: perform ongoing tuning to adapt to different project data characteristics and annotation needs, improving model performance in data annotation tasks.
- Analyze and evaluate the effectiveness of models/tools, propose targeted improvement strategies, and drive the iterative upgrades of annotation models/tools.
Tags & Categories
Answer 10 quick questions to check your fit for 混元大模型标注算法研究员（北京） @ Tencent.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs