Machine Learning Engineer

Sydney, Remote. Posted 4 days ago

The role

You will deliver bespoke AI solutions for diverse clients. You will build and deploy production-grade ML software, tools, and infrastructure while contributing to scalable software architecture.

What you will do

Building and deploying production-grade ML software, tools, and infrastructure.
Creating reusable, scalable solutions that accelerate the delivery of ML systems.
Collaborating with engineers, data scientists, and commercial leads to solve critical client challenges.
Leading technical scoping and architectural decisions to ensure project feasibility and impact.
Defining and implementing Faculty's standards for deploying machine learning at scale.
Acting as a technical advisor to customers and partners, translating complex ML concepts for stakeholders.

Required qualifications

Understand the full machine learning lifecycle.
Experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch.
Strong Python skills.
Solid experience in software engineering best practices.
Hands-on experience with cloud platforms and infrastructure (e.g., AWS, Azure, GCP), including architecture and security.
Worked with container and orchestration tools such at Docker & Kubernetes to build and manage applications at scale.
Comfortable with core ML concepts, including probability, statistics, and common learning techniques.
Excellent communicator, able to guide technical teams and confidently advise non-technical stakeholders.
Thrive in a fast-paced environment.
Enjoy the autonomy to own scope, solve and delivery solutions.

Before you apply

Talent Team Screen (30 minutes)
Pair Programming Interview (90 minutes)
System Design Interview (90 minutes)
Commercial Interview (60 minutes)
Do not use AI to generate answers during live interviews.

About the company

Faculty was established in 2014 to work with global customers to transform performance through human-centric AI. They innovate, build and deploy responsible AI for clients in government, finance, retail, energy, life sciences and defence.