Data Engineer for AI Singapore

3 weeks ago

Singapore NATIONAL UNIVERSITY OF SINGAPORE Full time
Roles & Responsibilities

Interested applicants are invited to apply directly at the NUS Career Portal.

Your application will be processed only if you apply via NUS Career Portal.

We regret that only shortlisted candidates will be notified.


Job Description

AI Singapore (AISG) is the 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.

In the Industry Innovation pillar of AISG, we develop AI solutions and capability-building programmes to solve companies’ business problems, provide development platforms and tools, and grow the national talent pipeline to power Singapore's AI efforts.

Since our inception in 2017, we have established a culture of respect, continuous learning, experimentation and curiosity, with all our work centred around innovation. The candidate will join a talented team of AI engineers, data scientists, consultants, data engineers and platforms engineers, who are all inspired by the opportunity to work on emerging technologies and lead Singapore into an AI-powered future.

Candidates, especially seniors, will be expected to provide technical leadership, engage stakeholders independently, mentor junior engineers and apprentices, and contribute ideas to improve the system.

As a Data Engineer under the Platforms Engineering Group, you'll help build and operate modern infrastructures and systems to run large-scale machine learning and deep learning workloads. As part of the data engineering team, we oversee and standardise the data pipeline for our projects. You will also design, develop, and maintain the AISG platform and tooling stack to enable AIAP, 100E project teams, and Partners to build better and faster products. We continuously evaluate and adapt industry data components in our pipeline so that the team is equipped with relevant knowledge and working hand-in-hand with our Machine Learning Operations team-mates to provide our AI Engineers with the tools they need in model training.


Duties & Responsibilities

  • Evaluate, architect, deploy, and maintain data platform & tooling stack for empowering AISG engineers in carrying out their roles & responsibilities.
  • Mentor AISG apprentices and assist whenever needed in developing end-to-end data pipeline workflows to facilitate the AI lifecycle and ensure that solutions are delivered efficiently and sustainably.
  • Act as an intermediary between the Platforms Engineering and AI project teams.
  • Assist the InfraOps, MLOps and Experiences teams in building and maintaining production infrastructure to be resilient, secure, and high-performing.
  • Implement data infrastructure as code (IaC) processes to automate our systems' configuration, provisioning, deployment, and monitoring.
  • Collaborate with AISG’s partners to design, implement, and deploy new systems and improvements to existing systems.
  • Document and troubleshoot issues arising from our systems when they occur.
  • Develop tools and software that improve and automate data infrastructure provisioning.
  • Propose and drive technical decisions to completion for the aforementioned responsibilities, including documentation.
  • Mentor AISG Apprentices and others.
Qualifications
  • Excellent communication skills, including thoughtful listening skills and the ability to express complex ideas clearly and succinctly.
  • The ability to reason about engineering issues holistically using engineering fundamentals and knowledge about architecture.
  • Possess 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 engineering or infrastructure position for a minimum of 2 years.
  • Familiarity with data center environments and appreciation of data center operations.
  • Proficient in at least one commonly used programming language, such as Python, Ruby, Go, Rust, Javascript, Java, C#, etc.
  • Proficient in administering Linux systems.
  • Proficiency in at least one automation tool, such as Ansible, Chef, Puppet, Bash, PowerShell, etc.
  • Familiarity with virtualisation technologies such as KVM, VMWare, etc.
  • Familiarity with the container and container orchestration technologies such as Docker, rkt, Singularity, Kubernetes, Docker Swarm, 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, Delta Lake, Hive, Spark, Hadoop systems, job/workload schedulers, etc.
  • An aptitude for automated system design and implementation (automated deployments and automated testing).
  • The candidate should be comfortable conducting presentations and workshops. These will be aimed at disseminating complex data concepts and our technical architecture.




Tell employers what skills you have

Excellent Communication Skills
Machine Learning
Architecture
Programming language
Artificial Intelligence
Data Engineering
Distributed Systems
Automation Tool
Orchestration
Debugging

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