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Federated Learning Engineer for AI Singapore

Date: 01-Jul-2022

Location: Kent Ridge Campus, SG

Company: National University of Singapore

Job Description

AI Singapore (AISG) is a national AI programme launched by the National Research Foundation (NRF) to anchor deep national capabilities in Artificial Intelligence (AI). 

The programme office is hosted by the National University of Singapore (NUS) and brings together all Singapore-based research institutions and the vibrant ecosystem of AI start-ups and companies developing AI products to perform use-inspired research, grow the knowledge, create the tools, and develop the talent to power Singapore’s AI efforts.


AI Singapore is looking for an individual to join us as a Federated Learning Engineer. As a Federated Learning Engineer under the Platforms & Products team, you will help design, and build the open sourced federated learning platform wholly owned and developed within AISG. You will also design, develop, and deliver federated learning solutions to external partners and industry collaborators to complement their machine learning pipelines.

1.    Be part of a team that develops a production grade federated learning platform.
2.    Implement new features and functionality for the platform.
3.    Improve system design and architecture to ensure high stability, performance and reliability of the product.
4.    Champion good code quality practices towards reliable, performant and maintainable solutions.
5.    Participate in creating technical specifications and performing code reviews with other engineers
6.    Participate in agile planning and scope estimation for team projects
7.    Generate and maintain documentation as needed
8.    Mentor AISG Apprentices and other team members working on industrial projects.


•    Excellent communication skills, including thoughtful listening skills and expressing complex ideas clearly and succinctly.
•    The ability to reason engineering issues holistically using engineering fundamentals and knowledge about architecture.
•    A systematic approach to development and engineering, such as debugging or object-oriented design, DevOps and MLOps practices, and agile software development.
•    Have held at least one software engineering position for a minimum of 3 years.
•    Strong proficiency in Python programming language, data structures, multi-threaded and asynchronous architectures.
•    Ability to translate algorithms from papers to code.
•    Proficient in machine learning frameworks such as PyTorch and Tensorflow.
•    Proficient in administering Linux or Unix-based systems.
•    Proficient in HTML5, CSS and Javascript frameworks such as React and Angular is preferred.
•    Familiarity with distributed computing frameworks such as Dask, Ray and PySyft.
•    Familiarity with the container and container orchestration technologies such as Docker, Docker-compose, Kubernetes, Helm, etc.
•    Familiarity with AWS, Microsoft Azure, Google Cloud Platform, and cloud deployment tools.
•    Familiarity with distributed systems and related technologies and tools such as high-performance computing cluster systems, Hadoop systems, job/workload schedulers, etc.
•    Willing to learn, understand and accept the principles and constraints of Federated Learning, and apply it during development.
•    An aptitude for automated deployments and automated testing, CI/CD pipelines.

Covid-19 Message

At NUS, the health and safety of our staff and students are one of our utmost priorities, and COVID-vaccination supports our commitment to ensure the safety of our community and to make NUS as safe and welcoming as possible. Many of our roles require a significant amount of physical interactions with students/staff/public members. Even for job roles that may be performed remotely, there will be instances where on-campus presences are required. 

In accordance with Singapore's legal requirements, unvaccinated workers will not be able to work on the NUS premises with effect from 15 January 2022. As such, job applicants will need to be fully COVID-19 vaccinated to secure successful employment with NUS.

More Information

Location: Kent Ridge Campus

Organization: Office of the Deputy President(Res&Tech)

Department : AI Singapore

Employee Referral Eligible: No

Job requisition ID : 12686