Senior Machine Learning Engineer

EatClub

. Build and maintain the feature store, model deployment pipelines, Databricks experimentation environment, and model serving layer .

Posted 9/18/2026full-timeBondi Junction • AustraliaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining feature stores, model deployment pipelines, and serving APIs, with a strong focus on MLOps practices and production software engineering. Proficient in translating modeling requirements into production systems while ensuring platform reliability and performance.

Highest-signal resume keywords

MLOps ExperiencePython FluencyDatabricks ProficiencyAPI Design ExperienceAWS Services Knowledge

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Hard Skills

Model DeploymentFeature Store DesignWorkflow OrchestrationExperiment TrackingMonitoringDrift DetectionForecasting LiteracyQuantile LossTime-Series Cross-ValidationBackend Engineering

Soft Skills

Exceptional Communication SkillsBias to Action

Tools & Technologies

DatabricksAWSClaude CodeLLMVector-DB

Industry Keywords

HospitalityRetailDemand ForecastingMarketplace

Tech Stack

Tools & technologies

AWSPython

About the role

Key responsibilities & impact

Build and maintain the feature store, model deployment pipelines, Databricks experimentation environment, and model serving layer
Translate modelling requirements into production systems with the Senior Data Scientist
Define contracts between feature engineering and feature serving, and between model training and model deployment
Own POS data pipelines and downstream serving APIs with backend engineers
Collaborate with the Product Manager on platform reliability, priorities, and future flexibility
Engage with restaurant operators to understand the impact of latency, stale data, and broken pipelines
Own model deployment end to end, including versioning, rollout, rollback, monitoring, and drift detection
Design and operate serving APIs that expose forecasts in the product
Productionise modelling approaches and benchmark compute footprint, latency, and cost
Build infrastructure for variance attribution and LLM/vector-DB-based forecast explainability
Advance the team’s AI-first workflow with agentic loops, asynchronous runs, and human final review
Support demand forecasting, affinity modelling, restaurant grouping, per-venue model selection, intraday demand serving, Actions Feed recommendations, and forecast confidence infrastructure

Requirements

What you’ll need

Exceptional communication skills for translating modelling requirements into system design
Strong Python and production software engineering fluency, including typed code, testing, CI/CD, and code review discipline
Deep end-to-end MLOps experience, including model versioning, deployment pipelines, workflow orchestration, experiment tracking, model serving, monitoring, and drift detection
Solid hands-on experience with Databricks or an equivalent platform
Feature store design and implementation experience, including online/offline consistency, freshness, and backfills
Strong grasp of AWS services relevant to ML infrastructure, including compute, storage, orchestration, and serving
API design and backend engineering experience
Forecasting/ML literacy, including quantile loss, exogenous regressors, and time-series cross-validation
Evidence of shipping production systems and a bias to action
AI-first working style using Claude Code, agentic workflows, and AI in the daily workflow
LLM, RAG, or vector-DB infrastructure experience is an advantage
Experience building or scaling a feature store from scratch is an advantage
Hospitality, retail, demand-forecasting, or marketplace domain experience is an advantage
Breadth across ML engineering, data engineering, data science, analytics, and software engineering is an advantage
Experience setting up an ML platform or pairing with an existing data scientist is an advantage

Benefits

Comp & perks

Autonomy, flexibility, and a collaborative culture
Access to some of the best restaurants and hospitality leaders in the industry
Optional $5 voucher for first-time users who try EatClub using code ECAPPLY5; entirely voluntary and has no impact on the application or interview process