In-Demand Machine learning engineer Jobs in Parramatta, Nsw

Senior Machine Learning Engineer (Platform)
Neara —Sydney NSW
- Full-time
- Hybrid work
- Azure
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Research & Development Engineer
HEO —Sydney NSW
- $140,000 - $165,000 a year
- Full-time
- Doctoral degree
- Engineering
- AWS
- Parental leave
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Data Engineer
Optus —Sydney NSW
- SQL
- Parental leave
- Employee discount
7d
Senior Research Engineer
Canon —Sydney NSW
- Doctoral degree
- Research
- Presentation skills
- Free parking
6d
Microservices Engineer and AI Technical Architect - Sydney
Trideca —Sydney NSW
- Full-time
- Agile
- AI
- Leadership
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6d
Senior Databricks Consulting Engineer
Ultra Tendency —Sydney NSW
- Remote
- Spanish
- Azure
- Master's degree
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Senior Delivery Consultant: Agentic Software Engineer, AWS Professional Services
Amazon Web Services Australia Pty Ltd —Sydney NSW
- Full-time
- DevOps
- Systems design
- Databases
5d
Senior Software Engineer - Database Engineering
Snowflake —Barangaroo NSW
- Full-time
- Computer Science
- Engineering
- Master's degree
Senior Software Engineer, iOS, Google Photos
Google —Sydney NSW
- Full-time
- Doctoral degree
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3h
Senior Associate, Data Science & AI Solutions Global Markets
Commonwealth Bank —Sydney NSW
- Full-time
- Azure
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11d
Senior Manager, Data Analytics and AI Consulting
EPAM Systems, Inc. —Sydney NSW
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AI Engineering Manager
MYOB —Sydney NSW
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Forward Deployed Engineer, Generative AI, GECX, Google Cloud
Google —Sydney NSW
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Senior Azure Cloud Customer Experience Engineer - Japanese Speaking
Microsoft —Sydney NSW
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Lead Software & AI Engineering Consultant
DiUS —Sydney NSW
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Avanade —Sydney NSW
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Sourceo —Sydney NSW
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Forward Deployed Engineer, Generative AI, GECX, Google Cloud
Sourceo —Sydney NSW
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Senior Machine Learning Engineer (Platform)

Neara
Sydney NSW

Apply Now

Job Details

Full-time
13 hours ago

Qualifications

CI/CD
Data modelling
Azure
Google Cloud Platform
OS Kernels
AWS
Docker

Full Job Description

Imagine having the power to stress-test an entire power grid against a hurricane or thunderstorm before the clouds even gather. That is the reality we are creating at Neara.

We use advanced machine learning to create engineering-grade, physics enabled digital twins of electricity grids across four continents, this helps asset owners understand their biggest challenges and bring the most viable solutions to life across millions of kilometres of infrastructure.

By simulating extreme weather and structural stress at a network-wide scale, we empower the world’s largest utilities to pinpoint risks, optimise investments and build a more resilient global energy future.

Our team is a collection of brilliant minds who are fanatical about making a tangible difference in the real world, utilising AI and machine learning to accelerate everything from data classification to complex scenario analysis. We have built a special culture where innovation thrives because everyone owns the mission and we need smart, creative people to help us scale this impact to every corner of the globe.

The Senior MLOps Engineer builds and runs the pipelines, deployment systems, and observability that keep Neara's ML models training reliably and serving in production.

Neara is conducting cutting edge research, developing multi-modal spatial frontier models. You will help the team run faster, helping overcome challenges that have never been seen before in the world. These models work with a range of less researched data types, including point cloud, geospatial data, and asset data. The lack of research maturity in the geospatial domain and novel nature of the problem presents unique challenges around performance, data unification, and deployment.

The problem and role stretch beyond pure research. These models will be deployed with our global utility and new vertical customers, delivering real value and increased climate resilience for critical infrastructure. Your role will be critical in getting models out of the lab and into customer environments - reliably, repeatably, and economically.

WHAT YOU'LL DO

Build and operate ML pipelines - Own the training, evaluation, and deployment pipelines end-to-end, from data ingestion through to models running in customer environments.
Automate the path to production - Build CI/CD for models, artefact and model registries, reproducible environments, and infrastructure as code that takes an experiment to a deployed service without manual steps.
Keep production models healthy - Implement monitoring, alerting, and drift and data quality checks, and act as a first responder when something breaks.
Run distributed training infrastructure - Manage GPU clusters and scheduling, keep jobs efficient and utilisation high, and troubleshoot failures across cloud, on-prem, and neocloud environments.
Ship reliable serving infrastructure - Deploy and scale inference services that handle spiky load across regions and customers, with attention to latency, cost, and data residency requirements.
Remove friction for the ML team - Improve the tooling and workflows ML engineers use daily, and document the standards that keep things consistent as the team grows.

WHAT YOU'LL BRING

Solid hands-on experience building and operating ML training pipelines, model serving, and monitoring systems in production.
Strong Python, and working knowledge of PyTorch (or equivalent) - enough to debug a training job, not necessarily to design the model.
Practical experience with distributed training and GPU infrastructure, including scheduling, resource management, and diagnosing throughput or memory issues.
Experience in the cloud (AWS, GCP, or Azure), container orchestration (Kubernetes, Docker), and infrastructure as code.
Experience with production model monitoring, data quality frameworks, and preparing training data for ML readiness.
Sound engineering judgement - you write maintainable code, think about failure modes, and know when a quick fix is fine and when it isn't.
Bonus: CUDA or kernel-level optimisation experience, exposure to point cloud or geospatial data, or experience supporting deployments into regulated or air-gapped customer environments.

WHAT'S IN IT FOR YOU?

Competitive salary
Meaningful ESOP
Fully Flexible Work Environment. We have a fully stocked office (and an impressive snack collection) in Redfern.
Regular office events
The real benefit is working on a genuinely complex, innovative and industry-leading product, making a genuine difference in the world around us

To apply, please use the online application link below. Neara values diversity, belonging and equal employment opportunities. We encourage individuals from all backgrounds to apply.

No agencies or third-party service providers, please.
#LI-AP1

Apply Now

Refine Your Search

machine learning engineer jobs in parramatta, nsw

Senior Machine Learning Engineer (Platform)

Research & Development Engineer

Data Engineer

Senior Research Engineer

Microservices Engineer and AI Technical Architect - Sydney

Senior Databricks Consulting Engineer

Senior Delivery Consultant: Agentic Software Engineer, AWS Professional Services

Senior Software Engineer - Database Engineering

Senior Software Engineer, iOS, Google Photos

Senior Associate, Data Science & AI Solutions Global Markets

Senior Manager, Data Analytics and AI Consulting

AI Engineering Manager

Forward Deployed Engineer, Generative AI, GECX, Google Cloud

Senior Azure Cloud Customer Experience Engineer - Japanese Speaking

Lead Software & AI Engineering Consultant

Artificial Intelligence (AI) Engineering Senior Consultant

Engineering Manager, Technical Lead, Google Photos

Forward Deployed Engineer, Generative AI, GECX, Google Cloud

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