ML Solutions Engineer - Melbourne - $180,000 - Gain Gen AI and Agentic AI

Salary:

$150000 - 180000

/ Year

Contract Type:

Permanent

Location:

Melbourne - VIC

Industry:

Software Development

Reference:

39585231

Contact Name:

Contact Email:

info@techanddatapeople.com

Date Published:

03-Sep-2025

ML Solutions Engineer - Melbourne - $180,000 - Gain Gen AI/Agentic AI

Tech and Data People are working with a company who are recognised as being at the forefront of Advanced Analytics and AI. We’re looking for a skilled Machine Learning & Cloud Engineer to join our innovative technology team. This is a full-time opportunity to design and scale next-generation AI infrastructure that powers advanced analytics and intelligent automation.

What You’ll Do

Design and optimise data pipelines and backend services to support large-scale machine learning systems.
Build and maintain cloud infrastructure with CI/CD automation to enable rapid and reliable deployments.
Translate experimental models into production-ready, high-performance ML solutions.
Collaborate with cross-functional teams and stakeholders to define technical requirements and deliver impactful solutions.
Lead improvements in code quality, engineering practices, and scalability.
Troubleshoot complex data and infrastructure challenges to ensure robust system performance.
Develop secure, well-structured Python-based back-end services and custom integrations using APIs.
Research emerging technologies to advance AI engineering practices and optimise performance.
Enhance system monitoring, testing, and continuous integration practices.

What We’re Looking For

Proven engineering experience in cloud-native environments, with exposure to machine learning systems.
Hands-on experience in cloud services (Azure, AWS, or similar) and modern data platforms.
Proven skills in CI/CD pipeline design, automation, and orchestration (Docker, Kubernetes, or related).
Proficiency in Python for building robust backend systems (beyond scripting).
Experience with data modelling, APIs, and custom integrations between distributed systems.
Strong understanding of testing, benchmarking, and performance optimisation.
Excellent problem-solving, communication, and team collaboration skills.
Familiarity with ML lifecycle tools (MLFlow, Azure ML, or similar).
Experience with infrastructure as code (IaC) and SaaS-based architectures.
Knowledge of MLOps practices, including model monitoring and retraining workflows.

If you're interested in discussing this opportunity further or would like a more general chat about your career, get in touch and we can arrange a time.

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