Senior ML Engineer — Real-Time Dining AI Platform

EatClub; Sydney; On-site; AUD 180,000 - 230,000; Full time

Job summary

EatClub is seeking a Senior Machine Learning Engineer in Sydney to own the feature store, model deployment pipelines, and Databricks experimentation environment. You will design and operate serving APIs delivering real-time forecasts to restaurant operators, collaborating closely with data scientists and backend engineers.

The role emphasizes end-to-end production readiness, scalable ML infra, and AI-first workflows.

Qualifications

• Strong Python and production software engineering fluency.
• Deep MLOps experience: model versioning, deployment, monitoring and drift detection.
• Hands-on Databricks experience as experimentation/production environment.
• Experience building feature stores and end-to-end ML pipelines.
• Knowledge of AWS services for ML infrastructure and API design.

Responsibilities

• Stand up or harden the feature store, the default for the Senior Data Scientist.
• Own the model deployment pipeline end to end: versioning, rollout, rollback, monitoring.
• Build and maintain the Databricks-based experimentation environment.
• Design and operate the serving APIs that turn forecasts into usable UI data.
• Productionise new modelling approaches; benchmark compute, latency, and cost.
• Build infrastructure for variance attribution and vector-DB explanations.
• Advance AI-first workflows: agentic loops and async runs.
• Tackle hard systems problems and review work with the Senior Data Scientist.

Skills

Python

MLOps

Databricks

Model deployment

Feature store

AWS

API design

Time-series forecasting

CI/CD

AI tooling

Tools

Databricks

AWS

Job description

EatClub is seeking a Senior Machine Learning Engineer in Sydney to own the feature store, model deployment pipelines, and Databricks experimentation environment. You will design and operate serving APIs delivering real-time forecasts to restaurant operators, collaborating closely with data scientists and backend engineers.

The role emphasizes end-to-end production readiness, scalable ML infra, and AI-first workflows.