Machine Learning Engineer (SaaS)

TL;DR

Machine Learning Engineer (SaaS): Designing and optimizing the infrastructure and tooling powering data science and product workflows with an accent on automated ML pipelines and scalable backend systems. Focus on building predictive time-series models, scalable APIs using FastAPI, and event-driven cloud architecture on GCP.

Location: Hybrid (Melbourne or Sydney, Australia)

Company

hirify.global is an early-stage B2B SaaS startup building a universal business growth decision engine to help marketing and finance teams optimize sustainable growth.

What you will do

• Develop and refine time series models for accurate forecasting and outcome comparisons.
• Build and scale constraint-based optimization frameworks to support customer decision-making.
• Design and maintain scalable backend systems and APIs using FastAPI and SQLAlchemy.
• Architect event-driven systems on GCP using Cloud Run, Pub/Sub, and BigQuery.
• Manage parallel, multi-customer workloads using IaC (Pulumi/Terraform) and Kubernetes.

Requirements

• Experience building production systems and taking POCs to production.
• Proficiency in Python and ML libraries such as scikit-learn, pandas, PyTorch, or TensorFlow.
• Hands-on experience with GCP, Docker, and Kubernetes.
• Strong knowledge of CI/CD practices, testing, and maintainable code standards.
• Must be based in or able to work from the Melbourne or Sydney offices (Hybrid).

Culture & Benefits

• Equity options (ESOP) for all staff.
• Generous annual leave starting at 20 days, increasing up to 30 days.
• Paid parental leave for both primary and secondary caregivers.
• Flexible perk: 6 weeks of "work from anywhere" per year.
• High level of autonomy to lead initiatives from design through implementation.