分布式计算研发工程师-Ray（深圳/北京/上海）
Tencent
分布式计算研发工程师-Ray（深圳/北京/上海）
Job Description
分布式计算研发工程师-Ray（深圳/北京/上海）
📋 Job Overview
Tencent is seeking a Distributed Computing R&D Engineer specializing in Ray to develop a leading universal distributed computing engine based on the open-source Ray project. The role involves supporting Data + AI scenarios such as data science, large model training pipelines, AI agents, and privacy computing. Responsibilities include deep integration with K8S for cloud-native scalability and contributing to open-source collaborations to enhance industry influence.
📍 Location: Beijing, China
🏢 Business Unit: TEG
📄 Full Description
1.基于开源项目 Ray，打造业内领先的通用分布式计算引擎，包括但不限于以下方向：引擎内核（分布式Task调度与执行）、分布式数据处理框架、分布式在线服务编排框架等；
2.面向 Data + AI，支持和拓展以 Ray 为 infra 的多种业务场景，包括但不限于以下方向：数据科学、大模型训练数据管道服务、在线推理与离线推理、AI Agent与应用系统、隐私计算、图计算等；
3.与 K8S 深度融合，建设云原生环境下超大规模分布式系统的服务能力与平台化能力，为业务提供高可用、可扩展、高易用性的集群化服务；
4.参与开源共建与合作，提升团队与个人在业界的影响力。
2.面向 Data + AI，支持和拓展以 Ray 为 infra 的多种业务场景，包括但不限于以下方向：数据科学、大模型训练数据管道服务、在线推理与离线推理、AI Agent与应用系统、隐私计算、图计算等；
3.与 K8S 深度融合，建设云原生环境下超大规模分布式系统的服务能力与平台化能力，为业务提供高可用、可扩展、高易用性的集群化服务；
4.参与开源共建与合作，提升团队与个人在业界的影响力。
🎯 Key Responsibilities
- Develop the core engine kernel for distributed task scheduling and execution based on Ray
- Build distributed data processing and online service orchestration frameworks
- Support and expand Data + AI business scenarios including data science, large model training pipelines, online/offline inference, AI agents, privacy computing, and graph computing
- Integrate deeply with K8S to construct high-availability, scalable, and user-friendly cluster services in cloud-native environments
- Participate in open-source co-building and collaborations to elevate team and personal industry influence
✅ Required Qualifications
- Strong background in distributed systems and computing
- Experience with open-source projects, particularly Ray
- Proficiency in cloud-native technologies like K8S
⭐ Preferred Qualifications
- Experience in AI and data science applications
- Knowledge of privacy computing and graph computing
- Contributions to open-source communities
🛠️ Required Skills
- Distributed task scheduling and execution
- Distributed data processing frameworks
- Online service orchestration
- AI infrastructure and large model training
- Cloud-native development with K8S
- Open-source collaboration and contribution
Locations
- Beijing, 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
- Distributed task scheduling and executionintermediate
- Distributed data processing frameworksintermediate
- Online service orchestrationintermediate
- AI infrastructure and large model trainingintermediate
- Cloud-native development with K8Sintermediate
- Open-source collaboration and contributionintermediate
Required Qualifications
- Strong background in distributed systems and computing (experience)
- Experience with open-source projects, particularly Ray (experience)
- Proficiency in cloud-native technologies like K8S (experience)
Preferred Qualifications
- Experience in AI and data science applications (experience)
- Knowledge of privacy computing and graph computing (experience)
- Contributions to open-source communities (experience)
Responsibilities
- Develop the core engine kernel for distributed task scheduling and execution based on Ray
- Build distributed data processing and online service orchestration frameworks
- Support and expand Data + AI business scenarios including data science, large model training pipelines, online/offline inference, AI agents, privacy computing, and graph computing
- Integrate deeply with K8S to construct high-availability, scalable, and user-friendly cluster services in cloud-native environments
- Participate in open-source co-building and collaborations to elevate team and personal industry influence
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Answer 10 quick questions to check your fit for 分布式计算研发工程师-Ray（深圳/北京/上海） @ Tencent.
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分布式计算研发工程师-Ray（深圳/北京/上海）
Tencent
分布式计算研发工程师-Ray（深圳/北京/上海）
Job Description
分布式计算研发工程师-Ray（深圳/北京/上海）
📋 Job Overview
Tencent is seeking a Distributed Computing R&D Engineer specializing in Ray to develop a leading universal distributed computing engine based on the open-source Ray project. The role involves supporting Data + AI scenarios such as data science, large model training pipelines, AI agents, and privacy computing. Responsibilities include deep integration with K8S for cloud-native scalability and contributing to open-source collaborations to enhance industry influence.
📍 Location: Beijing, China
🏢 Business Unit: TEG
📄 Full Description
1.基于开源项目 Ray，打造业内领先的通用分布式计算引擎，包括但不限于以下方向：引擎内核（分布式Task调度与执行）、分布式数据处理框架、分布式在线服务编排框架等；
2.面向 Data + AI，支持和拓展以 Ray 为 infra 的多种业务场景，包括但不限于以下方向：数据科学、大模型训练数据管道服务、在线推理与离线推理、AI Agent与应用系统、隐私计算、图计算等；
3.与 K8S 深度融合，建设云原生环境下超大规模分布式系统的服务能力与平台化能力，为业务提供高可用、可扩展、高易用性的集群化服务；
4.参与开源共建与合作，提升团队与个人在业界的影响力。
2.面向 Data + AI，支持和拓展以 Ray 为 infra 的多种业务场景，包括但不限于以下方向：数据科学、大模型训练数据管道服务、在线推理与离线推理、AI Agent与应用系统、隐私计算、图计算等；
3.与 K8S 深度融合，建设云原生环境下超大规模分布式系统的服务能力与平台化能力，为业务提供高可用、可扩展、高易用性的集群化服务；
4.参与开源共建与合作，提升团队与个人在业界的影响力。
🎯 Key Responsibilities
- Develop the core engine kernel for distributed task scheduling and execution based on Ray
- Build distributed data processing and online service orchestration frameworks
- Support and expand Data + AI business scenarios including data science, large model training pipelines, online/offline inference, AI agents, privacy computing, and graph computing
- Integrate deeply with K8S to construct high-availability, scalable, and user-friendly cluster services in cloud-native environments
- Participate in open-source co-building and collaborations to elevate team and personal industry influence
✅ Required Qualifications
- Strong background in distributed systems and computing
- Experience with open-source projects, particularly Ray
- Proficiency in cloud-native technologies like K8S
⭐ Preferred Qualifications
- Experience in AI and data science applications
- Knowledge of privacy computing and graph computing
- Contributions to open-source communities
🛠️ Required Skills
- Distributed task scheduling and execution
- Distributed data processing frameworks
- Online service orchestration
- AI infrastructure and large model training
- Cloud-native development with K8S
- Open-source collaboration and contribution
Locations
- Beijing, 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
- Distributed task scheduling and executionintermediate
- Distributed data processing frameworksintermediate
- Online service orchestrationintermediate
- AI infrastructure and large model trainingintermediate
- Cloud-native development with K8Sintermediate
- Open-source collaboration and contributionintermediate
Required Qualifications
- Strong background in distributed systems and computing (experience)
- Experience with open-source projects, particularly Ray (experience)
- Proficiency in cloud-native technologies like K8S (experience)
Preferred Qualifications
- Experience in AI and data science applications (experience)
- Knowledge of privacy computing and graph computing (experience)
- Contributions to open-source communities (experience)
Responsibilities
- Develop the core engine kernel for distributed task scheduling and execution based on Ray
- Build distributed data processing and online service orchestration frameworks
- Support and expand Data + AI business scenarios including data science, large model training pipelines, online/offline inference, AI agents, privacy computing, and graph computing
- Integrate deeply with K8S to construct high-availability, scalable, and user-friendly cluster services in cloud-native environments
- Participate in open-source co-building and collaborations to elevate team and personal industry influence
Tags & Categories
Answer 10 quick questions to check your fit for 分布式计算研发工程师-Ray（深圳/北京/上海） @ Tencent.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs