System Engineer for ML Platform on a Cloud-like HPC Infrastructure (Data-Centric Focus)

Immigration Policy Lab; Singapore; On-site; SGD 120,000 - 180,000; Full time

Benefits offered by this job

TAFEP compliant workplace

Diverse international team

Job summary

Singapore-ETH Centre is seeking a System Engineer for the ML Platform on a Cloud-like HPC infrastructure with a data-centric focus. You will manage the ML platform to support the full research lifecycle, including data tokenization, model cartography, and validation; this role involves multi-tenant HPC environments and quarterly travel to collaborate with the Swiss team.

The ideal candidate has a background in computer engineering or CS, experience with microservices, Linux, CI/CD, and

Qualifications

• Bachelor’s degree or higher in computer engineering, CS or related field.
• Knowledge of microservice architecture.
• Linux administration skills.
• Automation tools and CI/CD ecosystems (Gitlab CI, Vault).
• Developing Ansible configurations.
• Versioning and CI/CD workflows such as ArgoCD.

Responsibilities

• Manage the ML platform with a data-centric focus across the research lifecycle.
• Support data-centric CI/CD pipelines with artifact provenance (link training data IDs, preprocessing logs, and hyperparameters to artifacts).
• Use automation frameworks (Ansible) to manage modular vService integrations, enabling Token-Cartographer components in research environments.
• Ensure platform observability makes data and latent space embeddings visible and queryable for researchers.
• Maintain interfaces to infrastructure provisioning APIs for dynamic, multi-tenant vCluster creation and resource allocation.
• Support end-to-end provisioning and management of the ML platform, including secret vaults, git runners, and centralized artifact repositories.

Skills

Microservice architecture

Linux administration

Automation CI/CD

Ansible configurations

ArgoCD

Gitlab CI

HashiCorp Vault

Communication skills

Education

Bachelor's degree or higher in computer engineering, computer science, or related field

Tools

Gitlab CI

HashiCorp Vault

Ansible

Job description

System Engineer for ML Platform on a Cloud-like HPC Infrastructure (Data-Centric Focus)

100%, Singapore, fixed-term

The Singapore-ETH Centre was established in 2010 by ETH Zurich - The Swiss Federal Institute of Technology and Singapore’s National Research Foundation (NRF), as part of the NRF’s CREATE campus. As ETH Zurich's only research centre outside of Switzerland, the centre has strengthened the research capacity of ETH Zurich to develop sustainable solutions to global challenges in Switzerland, Singapore and the surrounding regions.

Set in Asia, in a rapidly urbanising region, the Singapore-ETH Centre aims to provide practical solutions to some of the most pressing challenges on urban sustainability, resilience and health through its programmes: Future Cities Lab Global and Future Health Technologies.

The centre serves as an intellectual hub for research, bringing together principal investigators and researchers from diverse disciplines and backgrounds. To promote the exchange of ideas and expertise, our researchers actively collaborate with universities and research institutes and engage with industry and government agencies to translate knowledge to practical solutions to real-world problems.

Project background

The AIS Instrumentation Gym is a multi-tier ML platform being built by both the National University of Singapore and the Singapore-ETH Centre (SEC) for shared scientific instruments (e.g., electron microscopy, X-ray imaging, and light microscopy). It supports researchers across three compute scales: laptop-based prototyping (S-Gym), single-GPU workstations (M-Gym), and multi-node HPC at the National Supercomputing Centre Singapore (L-Gym).

The Gym's purpose is to close the gap between high-dimensional scientific data and hypothesis generation. It does this by turning raw imaging data into learned, interpretable representations that scientists can explore as navigable landscapes: making patterns, anomalies, and structure legible at scales human intuition can no longer reach unaided.

As an ecosystem, the Gym brings together domain scientists, ML researchers, and systems builders around a common platform. We are now hiring full-time engineers and researchers to build, validate, and scale it.

Job description

As a System Engineer for ML Platform on a Cloud-like HPC Infrastructure (Data-Centric Focus) you will:

• Manage the ML platform with a data-centric focus, ensuring infrastructure supports the full research lifecycle—from data tokenization to model cartography and validation - rather than just code deployment.
• Support data-centric CI/CD pipelines that ensure the automatic logging of artifact provenance (linking specific training data IDs, preprocessing logs, and model hyperparameters to deployment artifacts).
• Use automation frameworks (Ansible) to manage modular vService integrations, allowing the seamless incorporation of Token-Cartographer components (e.g., tokenization and alignment modules) into research environments.
• Ensure platform observability makes data and latent space embeddings visible and queryable for researchers throughout the model's lifetime.
• Maintain the interface to the infrastructure provisioning APIs to support dynamic, multi-tenant vCluster creation and resource allocation.
• Support the end-to-end provisioning and management of the ML platform, including secret vaults, git runners, and centralized artifact repositories.

Position requires quarterly travel to Switzerland to synchronise with the core Swiss team. Join us to operate an ML platform at the bleeding edge of innovation, driving impact within a world-class tech stack.

Profile

Must-haves:

• A bachelor’s degree or higher in computer engineering, computer science, a relevant technical field, or equivalent practical experience.
• You should have a knowledge of:

1. Microservice architecture
2. Linux administration skills
3. Automation tools and framework, including CI/CD processes and ecosystem (e.g., Gitlab CI, HashiCorp Vault)
4. Developing Ansible configurations
5. Versioning systems and CI/CD workflows such as ArgoCD

Preferred:

• Understanding of "Data-Centric" ML principles (e.g., ensuring data quality, lineage, and versioning are first-class citizens in CI/CD).
• Experience building CI/CD pipelines for modular scientific/ML libraries or containerized research workflows.

1. Self-motivated and proactive team player
2. Strong communication skills or interest in developing them
3. Strong problem-solving mindset with tolerance for uncertainty and change
4. Understands user needs and works collaboratively to address them
5. Adaptive and willing to learn new technologies with and from others
6. Comfortable tackling complex or ambiguous problems
7. Comfortable admitting when you don’t know, reaching out and leveraging the right expertise when needed

• Project management and methodology:

1. Experience with working in self-organised teams
2. Familiarity with Agile methodology
3. Experience with test-driven development is a plus

Workplace

Workplace

We offer

• Accredited with 5 Tripartite Standards by Tripartite Alliance for Fair & Progressive Employment Practices (TAFEP) Singapore.
• A diverse workplace with 32 nationalities, offering ample opportunities for mutual learning.