AI Models Engineer for Production Healthcare AI

Heidi Health Corp.; Australia; Hybrid; AUD 90,000 - 130,000; Full time

Benefits offered by this job

Annual learning budget

Health & wellness allowance

Home office budget

Parental leave (26 weeks)

Fertility support

Work from anywhere 4 weeks/year

Equity

Job summary

Heidi Health Corp. seeks a mid-level engineer to own delivery across model customization, deployment, agent systems, and customer delivery. The role requires hands-on experience with production AI systems and openness to collaborating across areas to balance quality, cost, and latency.

You will work on customer-specific AI deployments, evaluate models, and ensure reliable performance while coordinating with customers and internal teams.

Qualifications

• Experience across at least two areas: model customization, deployment, agent systems, or customer delivery.
• Experience building or operating production AI systems.
• Solid software or ML engineering skills and understanding of open-weight LLMs.

Responsibilities

• Model customization: turn customer use cases into training/evaluation plans.
• Select data, models, training approaches.
• Fine-tune and evaluate domain-specific models.
• Improve quality based on testing and production feedback.
• Deployment and inference: design cost-effective cloud or on-prem deployment.
• Choose infrastructure and serving configurations.
• Improve reliability, latency, and operating cost.
• Build monitoring, backup, and recovery processes.
• Agent systems: build workflows around language models.
• Connect models with customer data, tools, and existing systems.
• Add controls and observability for production use.
• Customer delivery: work with customers to understand requirements.
• Explain trade-offs between quality, cost, privacy.
• Help take solutions from discovery through production launch.

Skills

ML Engineering

Software Engineering

LLM Ecosystem

Job description

Heidi Health Corp. seeks a mid-level engineer to own delivery across model customization, deployment, agent systems, and customer delivery. The role requires hands-on experience with production AI systems and openness to collaborating across areas to balance quality, cost, and latency.

You will work on customer-specific AI deployments, evaluate models, and ensure reliable performance while coordinating with customers and internal teams.