Software Engineer

The role

You will deliver bespoke AI solutions by building and deploying production-grade machine learning software, tools, and infrastructure. You will collaborate with cross-functional teams to ensure technical feasibility and 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

• 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.
• Experience 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.
• Ability to thrive in a fast-paced environment.
• Ability to own scope, solve and delivery solutions.

About the company

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