GenAI & ML Engineer — Production AI in Sydney (Hybrid)

Pearson Carter Limited; Sydney; Hybrid; AUD 110,000 - 170,000; Full time

Benefits offered by this job

Hybrid working

Competitive salary

Job summary

Pearson Carter Limited is seeking an AI Engineer to design, build and deploy production-ready AI and machine learning solutions in Sydney. This hybrid role involves developing generative AI, LLM applications, automation, data workflows, and cloud integrations while collaborating with technical and business stakeholders.

The ideal candidate has 3 years of AI/ML/Software Engineering experience, strong Python skills, and hands-on experience with AI production deployments.

Qualifications

• 3 years’ experience in AI / Machine Learning / Software Engineering.
• Strong Python development skills.
• Experience with LLMs, Generative AI, or AI agents.
• Experience with APIs and cloud platforms.
• Understanding of machine learning and data engineering concepts.
• Experience deploying AI solutions into production.
• Strong problem-solving and communication skills.

Responsibilities

• Design and develop AI and machine learning solutions.
• Build and integrate LLM and Generative AI applications.
• Develop AI-powered automation and workflows.
• Work with APIs, data pipelines, and cloud platforms.
• Evaluate and optimise AI model performance.
• Deploy and maintain AI solutions in production.
• Collaborate with software engineers, data teams, and business stakeholders.

Skills

Python development

LLMs/GenAI

AI production deployment

APIs & cloud platforms

Problem-solving

Communication skills

Tools

APIs

Cloud platforms

Data pipelines

Job description

Pearson Carter Limited is seeking an AI Engineer to design, build and deploy production-ready AI and machine learning solutions in Sydney. This hybrid role involves developing generative AI, LLM applications, automation, data workflows, and cloud integrations while collaborating with technical and business stakeholders.

The ideal candidate has 3 years of AI/ML/Software Engineering experience, strong Python skills, and hands-on experience with AI production deployments.