Machine Learning Engineer

Job Title: Machine Learning Engineer (Contract)

Location: Melbourne/Sydney (Hybrid)

Contract Duration: Until September 2025 (Potential Extension)

Overview:

We are seeking a highly skilled and motivated Machine Learning Engineer (Contract) to assist with both project and ongoing operations work.. This is an exciting opportunity for an experienced ML Engineer with a strong focus on MLOps, DevOps, and cloud technologies, especially Azure. The ideal candidate will have hands-on experience with Python web applications, containerization (Docker & Kubernetes), CI/CD pipelines, and a good understanding of ML pipelines and orchestration.

In this role, you will primarily support the migration project from legacy Docker clusters to Kubernetes, working alongside a talented team of engineers, data scientists, and other tech professionals. You will also assist in developing data products, ensuring the smooth operation of existing applications, and supporting the high-priority GenAI projects.

Key Responsibilities:

• MLOps & DevOps Support: Assist in the deployment and orchestration of machine learning and web applications, focusing on infrastructure, containerization, and CI/CD pipelines.
• Cloud & Containerization: Work extensively with Azure, Kubernetes, and Docker to deploy applications and services in a scalable and efficient manner.
• Python Web Applications: Support the development of backend applications, predominantly written in Python, with some exposure to Flask and FastAPI.
• ML Pipelines: Have a solid understanding of how machine learning pipelines work and how to integrate them into production environments.
• Project Support: Contribute to two large projects:
• Migration of legacy Docker cluster applications to Kubernetes, with a focus on Python-based backend services.
• Support GenAI projects, collaborating with various teams, including data scientists and backend engineers.
• CI/CD Pipelines: Manage and optimize GitHub and Jenkins pipelines for continuous integration and deployment.
• Legacy System Support: Maintain and provide operational support for legacy clusters, ensuring system reliability and stability.

Required Skills & Experience:

• 5-6 years of experience in software engineering, MLOps, or related roles, with a strong focus on DevOps practices.
• Experience with cloud platforms, particularly Azure.
• Proficiency in Python and experience developing Python web applications (Flask, FastAPI).
• Strong knowledge of containerization technologies (Docker and Kubernetes).
• Experience with CI/CD pipeline creation and management (GitHub, Jenkins, or equivalent).
• Batch scripting and ability to deploy applications efficiently.
• Familiarity with ML libraries in Python and the ability to work on ML pipelines and orchestration.
• Understanding of MLOps practices and tools used to support machine learning models in production.
• Knowledge of backend systems, and experience working in Linux environments.
• Strong problem-solving skills and the ability to quickly adapt to new technologies and challenges.
• Ability to work independently and take ownership of tasks with minimal guidance.
• Good communication skills and a collaborative attitude, working with cross-functional teams including data scientists, engineers, and stakeholders.
• Experience working with Kubernetes (preferred) and Docker.
• Previous experience with Flask and FastAPI for Python web applications.
• Exposure to data products and integrating machine learning models into business-critical applications.
• Experience in GenAI projects or other advanced AI applications.
• Prior experience working on migration projects, particularly in cloud or containerized environments

Key Projects:

• Migration Project: Transition from legacy Docker-based clusters to Kubernetes, ensuring smooth deployment and management of applications.
• GenAI Projects: Support high-priority GenAI initiatives, collaborating closely with various internal teams and data scientists.
• BAU Operations: Maintain and optimize legacy systems, ensuring infrastructure reliability and supporting ongoing ML development.

Benefits?

• Work alongside a talented team of software engineers, data scientists, and operations experts—one of the best teams tech-wise.
• Gain exposure to exciting, cutting-edge projects, including cloud migration and GenAI.
• Opportunity to work in a collaborative and dynamic environment where your expertise will be highly valued.