AI/ML Engineer: Production AI for Enterprise Ops

TaskVerse; Australia; On-site; AUD 110,000 - 180,000; Full time

Job summary

Mayvurn Arc is seeking an AI/ML Engineer to design, deploy, and improve AI systems that address real operational needs. You will work across the development lifecycle, collaborating with domain experts, engineers, and leadership to ship practical AI-enabled solutions in a fast-paced startup setting.

The role emphasizes hands-on problem-solving, translating workflows into AI workflows, and delivering production-ready ML systems that scale with business needs.

Qualifications

• At least two years of experience in AI/ML engineering, machine learning research, or a related field.
• Demonstrated experience taking AI/ML projects from concept through production.
• Strong engineering judgment for real-world product and operational needs.
• Product-oriented mindset with bias toward delivering useful outcomes.
• Ability to communicate clearly with non-technical users and experts.
• Comfort with ambiguity, changing priorities, and rapid iteration in a startup.

Responsibilities

• Design and build AI/ML systems that improve operational decisions.
• Translate complex processes into practical, AI-enabled workflows.
• Develop, test, deploy, and maintain ML solutions for production at scale.
• Collaborate with domain experts and users to validate assumptions and refine solutions.
• Connect technical decisions with customer needs and product priorities.
• Monitor performance and identify opportunities to improve reliability.
• Contribute to engineering practices and culture as the team grows.

Skills

AI/ML engineering

Production deployment

Cross-functional collaboration

Startup environment

Job description

Mayvurn Arc is seeking an AI/ML Engineer to design, deploy, and improve AI systems that address real operational needs. You will work across the development lifecycle, collaborating with domain experts, engineers, and leadership to ship practical AI-enabled solutions in a fast-paced startup setting.

The role emphasizes hands-on problem-solving, translating workflows into AI workflows, and delivering production-ready ML systems that scale with business needs.