Platforms Engineer, MLOps for AI Singapore (Innovation)

NATIONAL UNIVERSITY OF SINGAPORE; Singapore; On-site; SGD 70,000 - 90,000; Full time

Job summary

A leading educational institution in Singapore is seeking a Platforms Engineer (MLOps) to develop and maintain essential infrastructure for Machine Learning workflows. The ideal candidate will have a background in engineering, proficiency in programming languages like Python and Typescript, and experience with MLOps and container technologies. This role involves mentorship and collaboration in a dynamic team environment focused on advancing Singapore's AI capabilities.

Qualifications

• Minimum 2 years in an engineering or infrastructure role.
• Proficient in development and engineering practices.
• Basic understanding of machine learning.

Responsibilities

• Design and maintain platform tooling for engineers.
• Mentor apprentices and support MLOps workflows.
• Collaborate with teams for system improvements.

Skills

Communication skills

Engineering fundamentals

Development practices

Programming (Python, Typescript)

Linux systems administration

Machine learning concepts

Automation tools (Ansible, Terraform)

Container technologies (Docker, Kubernetes)

Job description

Interested applicants are invited to apply directly at the NUS Career Portal. Your application will be processed only if you apply via the NUS Career Portal. We regret that only shortlisted candidates will be notified.

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.

Since our inception in 2017, we have established a culture of respect, continuous learning, experimentation and curiosity, with all our work centered around innovation.

The Platforms Engineering team is looking for a Platforms Engineer (MLOps) to join us on our journey to build and operate modern on‑premise and cloud infrastructure and systems to enable and accelerate Machine Learning workflows for our internal teams.

In this role, you will focus on building and maintaining our internal MLOps platform across our on‑premise and cloud infrastructure. You will also serve as a domain expert to nurture AI talents and will play a key part in driving the growth of Singapore’s AI Sector.

Duties & Responsibilities

• Design, build and maintain platform & tooling stack that enables AISG engineers to deliver their roles & responsibilities effectively.
• Mentor AISG apprentices and support the development of end-to-end MLOps workflows to facilitate the AI lifecycle and ensure that solutions are delivered efficiently and sustainably.
• Serve as the liaison between the Platforms Engineering and AI project teams.
• Assist the InfraOps, DataOps and Experiences teams in building and maintaining production infrastructure to be resilient, secure, and high performing.
• Implement infrastructure-as-code (IaC) processes to automate our systems' configuration, provisioning, deployment, and monitoring.
• Collaborate with AISG partners to design, implement, and deploy new systems and improvements to existing systems.
• Maintain clear documentation of system issues and troubleshoot them promptly.
• Develop tools and software that improve and automate infrastructure provisioning.
• Propose and drive technical decisions to completion for the above responsibilities.

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.
• A systematic approach to development and engineering, such as debugging, DevOps and MLOps practices, and agile software development.
• Have held at least one engineering or infrastructure position for a minimum of 2 years.
• Proficient in at least one of the following programming languages: Python, Go, Rust, JavaScript/Typescript, etc. Proficiency in Python and Typescript is highly preferable.
• Proficient in administering Linux systems.
• Basic proficiency and understanding of machine learning concepts including data analysis, predictive modelling and model evaluation.
• Proficiency in at least one automation tool (Ansible, Terraform, Bash, PowerShell, etc.).
• Familiarity with the container and container orchestration technologies (Docker, rkt, Singularity, Kubernetes, Docker Swarm, Helm, etc.).