Staff ML Platform Engineer - Flexible Work & ESOP

Matchbox; Sydney; Hybrid; AUD 180,000 - 240,000; Full time

Benefits offered by this job

Competitive salary

Meaningful ESOP

Fully Flexible Work Environment

Job summary

Neara is hiring a Staff Machine Learning Platform Engineer to own the infrastructure enabling fast, reliable ML, serving and training at scale. You will tackle multi-modal spatial models and deploy them to utilities worldwide, enabling resilient energy infrastructure.

You will lead end-to-end platform strategy, build scalable tooling, and resolve bottlenecks across training, evaluation, and serving to accelerate frontier research into production.

Qualifications

• Hands-on experience building training pipelines, distributed compute, model serving, and monitoring systems at scale.
• Proficiency writing and optimising custom CUDA kernels for deep learning training, ideally across non-text/data types, with bottleneck diagnosis in sparse architectures.
• Production model monitoring, data quality frameworks, and training data warehouses brought to ML readiness.
• Ability to set ML platform standards, influence engineering roadmaps, and drive alignment on complex infra decisions across teams.
• Proficiency in Python and PyTorch; strong system design instincts and R&D grounding.

Responsibilities

• Own the ML platform strategy end-to-end - multi-year roadmap for training pipelines, serving, experiment management, and monitoring.
• Build tooling that accelerates ML delivery - establish infrastructure to move ideas to production faster, standardising workflows.
• Solve distributed systems problems - enable training across distributed data with residency and security requirements.
• Design scalable serving architecture - define systems that handle spiky production load while enabling regional experiments.
• Unblock the ML team at scale - define contracts/interfaces and roadmap to turn research into routine delivery.

Skills

ML Platform

Distributed systems

CUDA kernels

Python & PyTorch

Production ML monitoring

Cloud familiarity

Tools

CUDA

Kubernetes

Docker

PyTorch

AWS/GCP/Azure

Job description

Neara is hiring a Staff Machine Learning Platform Engineer to own the infrastructure enabling fast, reliable ML, serving and training at scale. You will tackle multi-modal spatial models and deploy them to utilities worldwide, enabling resilient energy infrastructure.

You will lead end-to-end platform strategy, build scalable tooling, and resolve bottlenecks across training, evaluation, and serving to accelerate frontier research into production.