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FedML (Fundational Ecosystem Design for Machine Learning) 公司完成千万级融资，正在招聘研发工程师、研究员、实习生等岗位。公司近期会研发四大机器学习训练平台(platform)及各行各业的解决方案(solution)，降低人工智能、海量数据、模型训练的门槛。福利对齐大厂，入职提供Macbook Pro顶配，欢迎投递简历。

Job – Back-end and Data Platform Software Engineer

Responsibilities

• Participate in the development of machine learning platform and open source communities
• Responsible for the foundational research and product development, and continuously improve the R&D efficiency
• Responsible for feature development, algorithm optimization of the platform, improving user experience and usability through cutting-edge or mature technologies
• Participate in or lead design reviews with peers and stakeholders to decide amongst available technologies;
• Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.

Minimum qualifications

• Bachelor’s degree or equivalent practical experience in computer science or related areas.
• 2 years of experience with software development in one or more programming languages (Python, Java, JavaScript, C/C++), or 1 year of experience with an advanced degree.
• 2 years of experience with data structures or algorithms in either an academic or industry setting.
• Good communication and writing skills in English environment.

Preferred qualifications

• Proficient in Java, familiar with Linux, Spring, Mybatis, Spring Cloud, MySQL, common NoSQL systems and distributed architecture;
• Familiar with the application of Kubernetes, Docker, DevOPS and other cloud native (Cloud Native) technologies, experience in medium and large-scale back-end application development is preferred, and experience in machine learning platform development is preferred
• Familiar with underlying middleware and distributed technologies (such as RPC framework, cache, message system, etc.);
• Familiar with the use/principle/tuning of common big data frameworks is preferred, such as Flume/Kafka/Hadoop/Hbase/Spark/Storm/ELK/ETL/kafka/Hive, etc.

Job – Researcher for Federated/Distributed Machine Learning/Systems

Responsibilities

• Participate in the development of machine learning platform and open source communities
• Responsible for the foundational research and product development, and continuously improve the R&D efficiency
• Responsible for feature development, algorithm optimization of the platform, improving user experience and usability through cutting-edge or mature technologies
• Participate in or lead design reviews with peers and stakeholders to decide amongst available technologies;
• Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.

Minimum qualifications

• Bachelor’s degree or equivalent practical experience in computer science or related areas.
• 2 years of experience with software development in one or more programming languages (Python, Java, JavaScript, C/C++), or 1 year of experience with an advanced degree.
• 2 years of experience with data structures or algorithms in either an academic or industry setting.
• Good communication and writing skills in English environment.

Preferred qualifications

• Mature research skills in machine learning or distributed/federated machine learning; be familiar with PyTorch or TensorFlow.
• Developing new algorithms or system-algorithm co-design for federated or distributed training platform
• Solve research challenges such as statistical or system heterogeneity, security, privacy for federated learning or distributed training platform
• Have at least two related paper published at the following top-tier machine learning or system conferences:

[Machine Learning] ICML, NeurIPS, ICLR;

[ML/AI Applications] CVPR/ECCV/ICCV, ACL/EMNLP, AAAI/IJCAI;

[Distributed/Cloud/Mobile/Database Systems] NSDI, OSDI, SOSP, SC, VLDB, MobSys, MobiCom, Sensys, HotOS, EuroSys, ICDCS, etc.

• Good communication skills with software engineers to land the developed algorithms into real-world system.

Job – Research Intern for Federated/Distributed Machine Learning/Systems

Responsibilities

• Participate in the development of machine learning platform and open source communities
• Responsible for the foundational research and product development, and continuously improve the R&D efficiency
• Responsible for feature development, algorithm optimization of the platform, improving user experience and usability through cutting-edge or mature technologies
• Participate in or lead design reviews with peers and stakeholders to decide amongst available technologies;
• Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.

Minimum qualifications

• Bachelor’s degree or equivalent practical experience in computer science or related areas.
• 2 years of experience with software development in one or more programming languages (Python, Java, JavaScript, C/C++), or 1 year of experience with an advanced degree.
• 2 years of experience with data structures or algorithms in either an academic or industry setting.
• Good communication and writing skills in English environment.

Preferred qualifications

• Good research skills in machine learning or distributed/federated machine learning; be familiar with PyTorch or TensorFlow.
• Developing new algorithms or system-algorithm co-design for federated or distributed training platform
• Solve research challenges such as statistical or system heterogeneity, security, privacy for federated learning or distributed training platform
• Have at least one related paper published at the following top-tier machine learning or system conferences:  
  [Machine Learning] ICML, NeurIPS, ICLR; 
  [ML/AI Applications] CVPR/ECCV/ICCV, ACL/EMNLP, AAAI/IJCAI; [Distributed/Cloud/Mobile/Database Systems] NSDI, OSDI, SOSP, SC, VLDB, MobSys, MobiCom, Sensys, HotOS, EuroSys, ICDCS, etc.

If you are interested, please email us with CV attached, briefly introduce your background, and explain why you would like to work with us (suggested email title: “Apply FedML – Position” for easier management).