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Senior Machine Learning Engineer (Platform)

nearaSydneyEngineering
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Salary
Not listed
Job type
Full-time
Work mode
Remote
Experience
Senior
Posted
7 Sept 2026
Status
Open · checked 8d ago

About this role

This position suits an experienced engineering professional with a strong background in production machine learning operations who wants to support critical infrastructure projects. Neara is hiring a Senior Machine Learning Engineer for a platform role located in Sydney.

Role Overview

Neara builds physics-enabled digital twins of electricity grids to help utility companies simulate extreme weather, manage risks, and optimize investments. The Senior MLOps Engineer designs and manages the deployment systems, pipelines, and observability tools required to keep machine learning models training reliably and serving production environments. This role bridges the gap between research and practical customer deployments for spatial frontier models.

Key Responsibilities

Own training, evaluation, and deployment pipelines from initial data ingestion through to customer environments.
Build continuous integration and deployment systems for models, maintain artefact and model registries, and establish infrastructure as code.
Implement system monitoring, alerting, data quality checks, and drift detection while acting as a first responder for incidents.
Manage GPU clusters, scheduling, and distributed training infrastructure across cloud, on-prem, and neocloud environments.
Deploy and scale inference services to handle varying regional loads with a focus on latency, cost, and data residency.
Enhance internal tooling, daily workflows, and documentation standards for the machine learning team.

Requirements

Hands-on background in building and maintaining production ML training pipelines, serving systems, and monitoring platforms.
Proficiency in Python along with working knowledge of PyTorch or equivalent frameworks for debugging training jobs.
Practical experience managing distributed training, GPU infrastructure, scheduling, and resource management.
Working knowledge of cloud platforms including AWS, GCP, or Azure, alongside container orchestration tools like Kubernetes and Docker, and infrastructure as code.
Experience establishing production model monitoring, data quality frameworks, and preparing data for machine learning readiness.
Sound engineering judgment with a focus on maintainable code and failure mode analysis.

Nice to Have

Experience with CUDA or kernel-level optimization.
Exposure to geospatial or point cloud data.
Background supporting deployments in air-gapped or regulated customer environments.

Skills and Tools

Python
PyTorch
Kubernetes
Docker
AWS, GCP, Azure
Infrastructure as Code
GPU Infrastructure
CUDA

Salary and Benefits

Competitive salary
Meaningful Employee Stock Ownership Plan
Fully flexible work environment with an office located in Redfern featuring a stocked snack collection
Regular office events

About the Company

Neara utilizes advanced machine learning to generate engineering-grade, physics-enabled digital twins of electricity grids across four continents. The company helps infrastructure asset owners simulate network-scale structural stress and extreme weather to identify risks and improve global energy resilience.

How to Apply

Interested candidates should apply directly on the official Neara careers page using the online application link provided in the original posting.

Skills and tech stack

PythonPyTorchKubernetesDockerAWSGCPAzureCUDAMLOpsMachine Learning

Questions candidates ask

Where is this job located?

This role is based in Sydney, with a fully flexible work environment and an office located in Redfern.

What is the primary focus of the role?

The Senior Machine Learning Engineer for the platform focuses on building and running pipelines, deployment systems, and observability to support machine learning models in production.

What technical skills are required?

Candidates need hands-on MLOps experience, strong Python skills, working knowledge of PyTorch or equivalent, experience with distributed training and GPU infrastructure, cloud familiarity, container orchestration like Kubernetes and Docker, and infrastructure as code.

Are there any preferred or bonus qualifications?

Bonus qualifications include CUDA or kernel-level optimization experience, exposure to geospatial or point cloud data, and experience supporting deployments in regulated or air-gapped environments.

What benefits are offered with this position?

Benefits include a competitive salary, meaningful ESOP, a fully flexible work environment, an office in Redfern with snacks, and regular office events.

Ready to apply?

The application is on the official neara careers page.

Apply on company site