Machine Learning Engineer
Opus Recruitment SolutionsSydney, Australia21 days ago
Job descriptionDeveloping models for classification, entity recognition, summarisation, and retrieval Customising and refining LLMs for specific business applications, ensuring optimal performance and scalability Collaborating with data engineering teams to prepare and transform large datasets for model training Building robust ML services with monitoring, retraining, and performance tracking capabilities Enhancing the organisation’s MLOps infrastructure, including model lifecycle management and evaluation systems Partnering with product and engineering teams to embed ML capabilities into core platforms Mid-Senior level Full-time Engineering and Information Technology Financial Services, Software Development, and Technology, Information and Media
Overview
This range is provided by Opus Recruitment Solutions. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range
A$140,000.00 / yr - A$200,000.00 / yr
Direct message the job poster from Opus Recruitment Solutions
Job title : Machine Learning Engineer
Location : Sydney, NSW
Salary : $140,000 - $200,000 Dependent on Experience
About the Company
Join a forward-thinking, innovation-led organisation based in Sydney that is investing heavily in AI and machine learning to solve how financial data is processed and understood. Operating at the intersection of AI and enterprise infrastructure, this company is building intelligent systems that extract meaning from complex, unstructured documents at scale.
This is not a research role. It’s a high-impact product engineering role in forward-deployed style where your work ships into production and is used by customers daily.
Key Requirements
Candidates should bring a minimum of five years’ experience in machine learning engineering, with demonstrable expertise in :
- Natural Language Processing (NLP), information extraction, and working with large language models (LLMs)
- Python programming and major ML frameworks such as PyTorch or TensorFlow
- MLOps practices including containerisation (Docker), orchestration (Kubernetes), and CI / CD pipelines tailored for ML workflows
- Utilising AI-enhanced development environments and tools to streamline experimentation and deployment
- Cross-functional collaboration with engineering, product, and business stakeholders
- Agile methodologies and fast-paced product development environments
- Exposure to modern ML tooling such as Modal, Weights & Biases, or Amazon SageMaker would be advantageous
Role Overview
The successful candidate will be responsible for designing and implementing machine learning solutions that interpret and structure unorganised financial data. This includes :
Machine Learning Engineer
Location : Sydney, NSW
Salary : $140,000 - $200,000 Dependent on Experience
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Machine Learning Engineer • Sydney, Australia
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