Senior ML Platform Architect

United States Digital Space LLC; Singapore; On-site; SGD 180,000 - 260,000; Full time

Benefits offered by this job

Term Life Insurance

Medical Insurance

GrabFlex

Parental leave

Birthday leave

LASA volunteering leave

Grabber Assistance Programme

FlexWork arrangements

Job summary

Grab is seeking a Principal Machine Learning Engineer on the AI Platform to act as the senior technical anchor and solution architect for the platform.

You will partner with engineering and research leads to shape the roadmap, evaluate productionizable SOTA techniques, and ensure cross‑team adoption with end‑to‑end ownership. This role drives large‑scale training, model serving, and platform consolidation, while mentoring engineers and translating user needs into practical platform requirements.

Qualifications

• Expert‑level mastery of ML lifecycle platforms and distributed training.
• Experience building scalable, multi‑tenant ML infrastructure.
• Hands‑on with LLM orchestration, fine‑tuning, or serving optimization.
• Ability to translate user pain into platform requirements and drive adoption.

Responsibilities

• Design end‑to‑end solutions on the AI Platform for data scientists and ML engineers.
• Drive large‑scale training throughput, reliability, and cost optimization
• Lead end‑to‑end model iteration from data through deployment and monitoring.
• Architect integrations across model serving, ML pipelines, and data serving.
• Translate user needs into platform requirements and enable cross‑team adoption.
• Create reference architectures and provide mentorship across the org.
• Stay current with SOTA ML infrastructure and guide roadmap decisions.

Skills

MLOps Expert

Distributed Systems

System Architecture

LLM Experience

AI Fluency

Ownership

Mentorship

Tools

Kubeflow

MLflow

Triton

TorchServe

PyTorch

Ray

Horovod

Job description

Grab is seeking a Principal Machine Learning Engineer on the AI Platform to act as the senior technical anchor and solution architect for the platform.

You will partner with engineering and research leads to shape the roadmap, evaluate productionizable SOTA techniques, and ensure cross‑team adoption with end‑to‑end ownership. This role drives large‑scale training, model serving, and platform consolidation, while mentoring engineers and translating user needs into practical platform requirements.