Principal ML & Data Platform Engineer — Real-Time

Preacta; Sydney; Presencial; AUD 180.000 - 280.000; Jornada completa

Descripción de la vacante

Preacta, a leading financial services organisation in Australia, is seeking a senior ML/engineering leader to direct data and AI platform development. You will set technical direction for data usage, with ML and decisioning as priorities.

You will design real-time and batch decisioning from customer signals, build the MLOps environment, and empower business teams with self-serve data pipelines and contracts.

Formación

• Senior, hands-on engineering role responsible for data and AI platform direction.
• Focus on real-time and batch decisioning using customer signals.
• Define governance, access control, and regulatory requirements within the platform.
• Shape self-serve data pipelines and data product sharing with contracts.
• Explore agentic workflows and AI-native data engineering.
• Coordinate with partner teams and vendors; influence architecture decisions.
• Mentor engineers and lead complex programs.

Responsabilidades

• Design real-time and batch decisioning to turn signals into actions.
• Build and maintain the MLOps environment.
• Shape self-serve data pipelines and publish data products.
• Establish engineering standards across batch/real-time/graphs/unstructured data.
• Embed governance and regulatory requirements into the platform.
• Drive DevOps/SRE practices in shipping.
• Lead with platform engineering lead on roadmaps; coach engineers.
• Explore agentic AI workflows to create datasets.

Conocimientos

ML engineering

Data engineering

Vendor influence

Regulated industry

Senior level

Real-time decisioning

Agentic AI

Descripción del empleo

Preacta, a leading financial services organisation in Australia, is seeking a senior ML/engineering leader to direct data and AI platform development. You will set technical direction for data usage, with ML and decisioning as priorities.

You will design real-time and batch decisioning from customer signals, build the MLOps environment, and empower business teams with self-serve data pipelines and contracts.