Lead Machine Learning Engineer

About the role

As a Lead Machine Learning Engineer, you will set the technical direction for complex AI/ML projects, ensuring models perform at scale and in production. You will lead the delivery of large-scale AI-powered platforms in high-risk environments while defining project roadmaps across multiple complex workstreams. This is an entrepreneurial leadership role where you will act as a trusted technical expert, guiding team priorities and defending architectural rationale to senior stakeholders.

Responsibilities

• Designing, implementing, and maintaining reliable, scalable ML systems while justifying key architectural decisions for production environments.
• Driving the development of shared libraries and infrastructure for model deployment, lifecycle management, and CI/CD pipelines.
• Leading model integration with infrastructure by creating APIs and services that enable scalable AI functionality in applications.
• Overseeing the delivery of multiple complex workstreams and defining project problems in high-risk environments.
• Ensuring reliable model performance by defining testing frameworks and model versioning systems for senior engineers to implement.
• Managing and coaching multiple individuals, setting team-wide development goals to improve technical depth and client delivery.
• Executing proactive recommendations for adopting new technologies and AI frameworks to maintain Faculty's competitive market position.

Required skills

• Machine Learning
• Cloud-native ecosystems
• Kubernetes
• CI/CD pipelines
• TensorFlow
• PyTorch
• System design
• API development

About the Company

Faculty was established in 2014 to transform performance through human-centric AI. They provide technical, product and delivery expertise to clients across government, finance, retail, energy, life sciences and defence.