Staff ML Platform Engineer — Scale AI for Global Grids

Neara; Singapore; On-site; SGD 164,000 - 255,000; Full time

Benefits offered by this job

Full relocation to Australia

Competitive salary

Meaningful ESOP

Job summary

Neara is seeking a Staff Machine Learning Platform Engineer to own the infrastructure that enables rapid, reliable ML at scale for cutting-edge digital twins of electricity grids.

You will build training pipelines, serving architectures, and monitoring systems, working with AWS/GCP/Azure, Kubernetes and CUDA kernels to push frontier models into production for global utility customers, with relocation to Australia.

Qualifications

• Significant technical experience running deep learning at scale.
• Experience in building training data warehouses and bringing data systems to ML readiness.
• Deep hands-on expertise building ML infrastructure at scale, in particular: training pipelines, distributed compute, model serving and monitoring.
• Strong proficiency in Python and PyTorch with a passion for deep learning.
• Ability to influence engineering roadmaps and drive alignment across teams.

Responsibilities

• Own the ML platform strategy end-to-end - Define and drive the multi-year technical roadmap for training pipelines, serving architecture, experiment management, and monitoring systems that tie it all together.
• Build tooling that accelerates ML delivery - Develop foundational infrastructure that takes engineers from idea to production faster, standardising workflows and eliminating friction between experimentation and deployment.
• Solve hard distributed systems problems - Enable training across distributed data with residency and security requirements, while ensuring models run efficiently across varied GPU hardware.
• Design scalable, flexible serving architecture - Define serving systems that handle spiky load in production while giving the ML team the freedom to experiment across regions, customers, tasks, and verticals.
• Unblock the ML team at scale - Identify what's slowing the team down, define the contracts and interfaces between training, evaluation, and serving, and build the roadmap to turn ambitious research into routine delivery.

Skills

Python

PyTorch

Distributed systems

Cloud infra

Kubernetes

Docker

CUDA

Data warehouses

Model serving

Experiment mgmt

MLP standards

S/W fundamentals

Tools

Kubernetes

Docker

AWS

GCP

Azure

Job description

Neara is seeking a Staff Machine Learning Platform Engineer to own the infrastructure that enables rapid, reliable ML at scale for cutting-edge digital twins of electricity grids.

You will build training pipelines, serving architectures, and monitoring systems, working with AWS/GCP/Azure, Kubernetes and CUDA kernels to push frontier models into production for global utility customers, with relocation to Australia.