Senior ML Engineer — Real-Time ML Platform & Deployments

Shoptalk; Sydney; On-site; AUD 140,000 - 190,000; Full time

Job summary

EatClub is seeking a Senior Machine Learning Engineer to own the feature store and deployment pipelines, and to drive the Databricks-based experimentation environment. You will collaborate with a Senior Data Scientist and backend engineers to turn modelling requirements into production systems and scalable ML infrastructure.

You will push AI-first workflows, design robust serving APIs, and evaluate new modelling approaches with attention to performance, latency, and cost in a hospitality-focused

Qualifications

• Strong Python and production software engineering fluency.
• Deep MLOps expertise covering versioning, deployment, monitoring and drift detection.
• Experience with Databricks or comparable platform for experimentation.
• Knowledge of AWS services relevant to ML infrastructure.
• Ability to design and own a serving layer and APIs.

Responsibilities

• Stand up or harden pieces of the feature store and deployment pipelines.
• Own the model deployment pipeline end-to-end: versioning, rollout, rollback, monitoring.
• Build and maintain the Databricks-based experimentation environment.
• Design and operate serving APIs turning forecasts into usable deliverables.
• Productionise new modelling approaches and assess compute and latency.
• Push AI-first workflows: agentic loops and async runs.
• Collaborate with data scientists and backend engineers to deliver scalable ML infra.

Skills

Python

MLOps

Databricks

AWS

Backend API

CI/CD

Forecasting

Model deployment

Feature store

Tools

Databricks

CI/CD tools

TensorFlow/PyTorch

Job description

EatClub is seeking a Senior Machine Learning Engineer to own the feature store and deployment pipelines, and to drive the Databricks-based experimentation environment. You will collaborate with a Senior Data Scientist and backend engineers to turn modelling requirements into production systems and scalable ML infrastructure.

You will push AI-first workflows, design robust serving APIs, and evaluate new modelling approaches with attention to performance, latency, and cost in a hospitality-focused