Principal ML Platform Engineer — Flexible Hours

Grab; Singapore; On-site; SGD 240,000 - 360,000; 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’s AI Platform team is seeking a Principal Machine Learning Engineer to own the platform and be the senior technical anchor. You will shape roadmaps, evaluate SOTA techniques, and drive cross-team implementations for scalable ML infra and LLM serving.

You will partner with Data Scientists and ML engineers to deliver end-to-end solutions, enable faster model iteration, and ensure reliable, cost-efficient training at scale on AIP’s platform.

Qualifications

• Expert-level mastery of ML lifecycle platforms and distributed training.
• Strong system design for scalable, secure multi-tenant services.
• Hands-on experience with LLM orchestration and fine-tuning infra.
• Ability to evaluate SOTA infrastructure paradigms and guide build vs skip.
• Proven track record mentoring senior engineers and driving ownership.

Responsibilities

• Design end-to-end solutions on AIP for data scientists and ML engineers.
• Drive large-scale training throughput, reliability, and cost considerations.
• Improve end-to-end model iteration time and quality for high-value use cases.
• Lead platform integrations across model serving, ML pipelines, and data services.
• Translate user pain into platform requirements and enable adoption.
• Create reference architectures and best-practice patterns for widespread use.
• Stay current with ML infra trends and mentor engineers across the org.

Skills

Advanced MLOps

ML Platform Eng

Kubernetes

Distributed Training

LLM Orchestration

System Architecture

Mentorship

Tools

Kubeflow

MLflow

Triton

TorchServe

Job description

Grab’s AI Platform team is seeking a Principal Machine Learning Engineer to own the platform and be the senior technical anchor. You will shape roadmaps, evaluate SOTA techniques, and drive cross-team implementations for scalable ML infra and LLM serving.

You will partner with Data Scientists and ML engineers to deliver end-to-end solutions, enable faster model iteration, and ensure reliable, cost-efficient training at scale on AIP’s platform.