Hybrid ML Engineer - Build Scalable ML Pipelines & Growth

Mutinex; Sydney; Hybrid; AUD 140.000 - 190.000; Vollzeit

Benefits dieser Stelle

ESOP

Parental Leave

Annual Leave

6 weeks work from anywhere

Zusammenfassung

Mutinex is hiring a Machine learning and Software Engineer to design, build, automate, and optimise ML pipelines powering data science workflows. You will work across infrastructure to internal tools, delivering end-to-end solutions in a hybrid environment across Sydney, Melbourne, and New York.

You’ll apply ML lifecycle expertise with Python, APIs, and cloud infrastructure to create reliable, observable, and scalable systems for customers worldwide.

Qualifikationen

• Experience building production systems and taking POCs to production.
• Skilled in APIs, CI/CD, testing, and deployment automation.
• Familiar with modern cloud infra (GCP), IaC tools like Pulumi or Terraform, and Docker/Kubernetes.
• Solid Python skills with hands-on ML tools: scikit-learn, pandas, PyTorch, TensorFlow.
• Strong craftsmanship: write clean, maintainable, and well-tested code.
• Curiosity and willingness to learn, fill knowledge gaps on the job.
• Startup mindset: align work with business goals and user needs.

Aufgaben

• Predictive Modelling and Forecasting: develop time series models for forecasting and decision support.
• Optimisation Frameworks: build scalable optimisation solving complex constraints for customer decisions.
• Backend API & Database Development: design scalable APIs, databases with FastAPI and SQLAlchemy; ensure CI/CD and clean code.
• Cloud Infrastructure & Orchestration: architect event-driven systems using Cloud Run, Pub/Sub, BigQuery; IaC and automated orchestration.

Kenntnisse

Python

ML lifecycle

APIs

CI/CD

Cloud platforms

Curiosity

Product mindset

Proactive problem solving

Tools

FastAPI

SQLAlchemy

Docker

Kubernetes

Pulumi

Terraform

GCP

scikit-learn

pandas

PyTorch

TensorFlow

Jobbeschreibung

Mutinex is hiring a Machine learning and Software Engineer to design, build, automate, and optimise ML pipelines powering data science workflows. You will work across infrastructure to internal tools, delivering end-to-end solutions in a hybrid environment across Sydney, Melbourne, and New York.

You’ll apply ML lifecycle expertise with Python, APIs, and cloud infrastructure to create reliable, observable, and scalable systems for customers worldwide.