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招聘【志愿搬运转需】[美国加州和深圳][支持远程]研发工程师、研究员、实习生等岗位

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晓晓挖掘姬
145阅读0评论2 个月前

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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).

招聘类型:
企业招聘
专业领域:
开发
工作方式:
远程工作
城市:
海外
需消耗电量 5
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