Data Scientist - ML Operations

Launch Recruitment Pty Ltd; Melbourne; On-site; AUD 129,000 - 185,000; Full time

Job summary

Launch Recruitment Pty Ltd in Melbourne is seeking a Data Scientist - ML Operations to advance production ML solutions in a cloud environment using AWS, Python and modern tooling. The role focuses on building, deploying and maintaining ML pipelines with emphasis on automation, testing and monitoring.

The contract position runs through June 2027 with a day rate to be determined by the market. Applicants must be Australian Citizens and located in Melbourne or willing to relocate.

Qualifications

• Experience building and maintaining ML pipelines.
• Deploying models into production using AWS services.
• Strong Python development skills.
• Experience working with large datasets, model development frameworks, testing practices.

Responsibilities

• Develop, deploy and operationalise ML models in production.
• Build and manage end-to-end ML pipelines and orchestration workflows.
• Collaborate with stakeholders and cross-functional teams to deliver scalable ML solutions.

Skills

Python development

ML pipelines

AWS SageMaker

Terraform

Docker

CI/CD

Testing & monitoring

Stakeholder engagement

Tools

Terraform

Docker

SageMaker

Job description

Data Scientist - ML Operations/Python/AWS

Melbourne | Contract Opportunity until June 2027
Must be Australian Citizen
Day rate - DOE

We are seeking an experienced Data Scientist - ML Operations to support the development, deployment and operationalisation of machine learning solutions within a cloud-based environment.

The successful candidate will have demonstrated experience building and maintaining machine learning pipelines and deploying models into production using AWS services. Strong Python skills are essential, along with hands-on experience working with large datasets, model development frameworks, testing practices, and automation of ML workflows.

Key skills and experience:

• Strong Python development skills including data science and machine learning libraries
• Experience with machine learning frameworks such as Scikit-learn, TensorFlow or PyTorch
• Hands-on AWS experience, including SageMaker and related cloud services
• Experience developing and managing ML pipelines and workflow orchestration tools
• Infrastructure as Code experience, ideally using Terraform
• Containerisation and deployment experience using Docker
• CI/CD and DevOps practices for machine learning solutions
• Experience implementing testing, monitoring and operational support for production ML models
• Strong stakeholder engagement and collaborative working skills

Highly regarded:

• Experience working with large-scale scientific, environmental or geospatial datasets
• Experience in secure, regulated or government environments
• Ability to obtain and maintain an Australian Government security clearance

This is an excellent opportunity to work on complex, data-driven initiatives within the public sector while contributing to the delivery of robust and scalable machine learning solutions.

Closing date Monday 26th October.

Must be in Melbourne and an Australian Citizen.