ML Solutions Engineer - Melbourne - $170,000 - 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.