Senior Platform And Machine Learning Engineer

Overview

Drive the evolution of a Single Customer View platform by architecting scalable recommendation engines and real-time data pipelines. You will lead the modernization of legacy systems into serverless cloud environments, bridging the gap between high-performance machine learning and robust DevOps practices.

Schedule: Full-time job / Flexible schedule during client business hours (Sydney, NSW)

Responsibilities

Machine Learning Platform & Architecture

• Productionize machine learning models in collaboration with Data Scientists, ensuring performance, scalability, and reliability.
• Design and maintain MLOps pipelines that automate model training, testing, validation, and deployment.
• Architect a Single Customer View platform that enables unified customer profiling and real-time decisioning.
• Build scalable cloud-based data warehouse architectures supporting analytics and machine learning workloads.
• Develop serverless functions and services using Python, Go, and SQL.

Data Engineering & Real-Time Processing

• Design and implement high-performance streaming data pipelines for real-time analytics and decision engines.
• Develop data ingestion pipelines using API integrations with retry and fault-tolerant mechanisms.
• Build optimized data models supporting both transactional and analytical workloads.
• Develop and maintain data orchestration workflows using modern workflow management tools.

Infrastructure, DevOps & Reliability

• Implement and maintain Infrastructure-as-Code (IaC) using Terraform to provision and manage cloud infrastructure.
• Build and optimize CI/CD pipelines to enable reliable and automated deployments.
• Apply Site Reliability Engineering (SRE) practices to maintain system availability and performance.
• Implement monitoring, alerting, and incident response systems for distributed applications.

Security, Compliance & Cost Optimization

• Implement secure identity and authentication frameworks for distributed cloud workloads.
• Ensure infrastructure and data pipelines comply with data privacy and security standards, including GDPR.
• Drive cloud cost optimization initiatives, including serverless architecture adoption and infrastructure rightsizing.
• Maintain clear and comprehensive technical documentation, including architecture diagrams and data lineage.

Requirements

Technical Skills

• Expert-level proficiency in Python and SQL
• Strong scripting experience using Shell
• Working knowledge of Go

Cloud & Data Platforms

• Strong experience working with Google Cloud Platform (GCP) services including: BigQuery, Vertex AI, Cloud Dataflow, Cloud Run, Google Kubernetes Engine (GKE), and Pub/Sub

Data Engineering

• Experience building large-scale data pipelines and streaming architectures
• Experience developing data warehouses and analytical data models
• Experience building real-time data processing systems

Infrastructure & DevOps

• Strong experience implementing Infrastructure-as-Code using Terraform
• Experience managing CI/CD pipelines using GitHub Actions or GitLab
• Experience with Cloud Build or Jenkins

Databases

• Hands-on experience with PostgreSQL-based databases
• Experience with NoSQL databases

Data & Analytics Tools

• Experience working with Airflow (DAG development)
• Experience using Looker / LookML
• Experience developing and managing API integrations

Independent Contractor Perks

• Permanent work from home
• Immediate hiring
• Health Insurance Coverage for eligible locations

Note

Please click the Apply button to complete your application, including the assessment questions, technical check, and voice recording. Your hourly pay rate will be established based on your performance in the application process; submissions with all requirements fulfilled will receive priority review.