Senior Machine Learning Engineer

Precision Sourcing; City of Melbourne; Hybrid; AUD 170,000 - 210,000; Full time

Job summary

Precision Sourcing is seeking a Senior ML/AI Engineer to build and deploy AI-driven solutions for real-world industrial challenges in Melbourne. You’ll own end-to-end development from data ingestion to production deployment, delivering systems that impact live operations.

The role rewards ownership, fast execution, and practical impact, with opportunities to grow into Lead or Head of ML as the business scales. Flexible work is available with some on-site days in Melbourne CBD.

Qualifications

• 6+ years of experience building AI/ML solutions.
• Strong background in machine learning and data-driven problem solving.
• Expert in Python (PyTorch, Tensorflow etc.) & SQL.
• Experience working with large datasets, particularly time-series or operational data.
• Experience deploying machine learning solutions into production environments.
• Strong software engineering fundamentals.
• Familiarity with cloud environments (Azure preferred).
• Ability to work independently and collaborate effectively across teams.

Responsibilities

• Develop and deploy machine learning solutions for industrial and energy use cases.
• Work with large-scale operational and time-series data to generate actionable insights.
• Collaborate with cross-functional teams to translate real-world challenges into AI-driven solutions.
• Contribute to the design of scalable, production-ready systems.
• Continuously improve model performance through monitoring, evaluation, and iteration.

Skills

Python

PyTorch

TensorFlow

SQL

Time-series data

Production deployment

Azure

Software engineering

Independent work

Education

Masters or PhD in ML/AI or related field

Tools

Azure

Git

Docker

Kubernetes

Job description

We are seeking a Senior ML/AI Engineer to join our team. This role is focused on building and deploying AI-driven solutions for real-world industrial challenges. You will work on high-impact problems where your models directly influence operational decisions in live environments.

This role is suited for someone who thrives on applying AI beyond theory and delivering systems that operate reliably in complex, dynamic settings. This role is for someone who enjoys taking ownership, moving fast, and building things that actually get used.

Ideally this person will grow with the business into Lead, Management or Head of Machine Learning and help grow the team as we expand and scale our business.

**Must be located in Melbourne and hold AU Permanent Residency or Citizenship.**

KEY RESPONSIBILITIES

• Develop and deploy machine learning solutions for industrial and energy use cases.
• Work with large-scale operational and time-series data to generate actionable insights.
• Collaborate with cross-functional teams to translate real-world challenges into AI-driven solutions.
• Contribute to the design of scalable, production-ready systems.
• Continuously improve model performance through monitoring, evaluation, and iteration.

REQUIRED EXPERIENCE

• 6+ years of experience building AI/ML solutions.
• Strong background in machine learning and data-driven problem solving.
• Expert in Python (PyTorch, Tensorflow etc.) & SQL.
• Experience working with large datasets, particularly time-series or operational data.
• Experience deploying machine learning solutions into production environments.
• Strong software engineering fundamentals.
• Familiarity with cloud environments (Azure preferred).
• Ability to work independently and collaborate effectively across teams.

PREFERRED EXPERIENCE

• Experience in industrial domains such as energy and manufacturing.
• Masters or PhD in a relevant field such as Machine Learning, Artificial Intelligence, Applied Mathematics, or a related discipline would be considered stronger.
• Exposure to real-world operational data (e.g. IoT, sensor, or system data).
• Understanding of the end-to-end ML/AI lifecycle and best practices

The office is based in Melbourne CBD and requires flexibility - some weeks can be remote, some you may need to be in 1-2 days, or if you are working on a mission critical release, you may want/need to be in 3-4 days.