Principal Machine Learning Engineer

MYOB

Melbourne

1 week ago

Melbourne

1 week ago

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Principal Machine Learning Engineer

MYOB seeks a Principal Machine Learning Engineer to design and scale AI-driven applications for their SaaS business management platform. This hybrid role in Melbourne involves leading a small team, building systems with LLMs and foundation models, and deploying on AWS. Requires expertise in machine learning frameworks, cloud-native experience, and MLOps.

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Hybrid

Full-time

Principal

Machine Learning Frameworks

TensorFlow

Salary

Not specified

Work Location

Melbourne, Victoria, Australia, AU

Work Model

Hybrid

Employment Type

Full-time

Experience Level

Principal

Core Qualifications

Technical (Must-have)

machine learning frameworksTensorFlowPyTorchLLMsfoundation modelsGPTClaudeLlamaAWSSageMakerBedrockS3CI/CD pipelines for MLmodel versioningmonitoringDockerKubernetes

Soft Skills

thought leadershipmentoringcoachingleading otherscustomer focusinnovationcreativityresilience

Key Responsibilities

•Design and implement machine learning systems from the ground up, focusing on LLMs and foundation models tailored to small business needs.
•Develop and deploy AI-powered features for automated document understanding, financial forecasting, and conversational interfaces.
•Optimise AI systems for scalability, safety, and reliability.
•Build from scratch: develop and optimise machine learning systems for small business accounting challenges.
•Deploy at scale: create scalable workflows to train, deploy, and monitor ML models on AWS services like SageMaker and Bedrock.
•End-to-end ownership: lead projects from ideation to production, implementing MLOps best practices.
•Collaborate and innovate with product managers, engineers, and stakeholders to align technical solutions with customer and business goals.

Machine Learning EngineerAILLMsFoundation ModelsAWSMLOpsSaaSHybridMelbourneMYOB

Key Responsibilities

•Design and implement machine learning systems from the ground up, focusing on LLMs and foundation models tailored to small business needs.

•Develop and deploy AI-powered features for automated document understanding, financial forecasting, and conversational interfaces.

•Optimise AI systems for scalability, safety, and reliability.

•Build from scratch: develop and optimise machine learning systems for small business accounting challenges.

•Deploy at scale: create scalable workflows to train, deploy, and monitor ML models on AWS services like SageMaker and Bedrock.

•End-to-end ownership: lead projects from ideation to production, implementing MLOps best practices.

•Collaborate and innovate with product managers, engineers, and stakeholders to align technical solutions with customer and business goals.