Senior Machine Learning Engineer

Nuage Technology Group; Sydney; On-site; AUD 80,000 - 120,000; Full time

Job summary

A dynamic scale-up is seeking a talented ML Ops Engineer to build and maintain the infrastructure for machine learning models. This role offers a unique opportunity to work on transformative technology that drives innovation and growth. You will be responsible for designing scalable ML infrastructure, automating deployments, and ensuring the reliability of ML systems in production. This is an exciting chance to collaborate with data scientists and engineers while optimizing resource efficiency. If you're passionate about ML Ops and eager to contribute to cutting-edge projects, this position is perfect for you.

Qualifications

• 4-5 years of experience in ML Ops or related roles.
• Strong understanding of ML lifecycle and deployment strategies.

Responsibilities

• Design and maintain scalable ML infrastructure.
• Automate deployment and monitoring of ML models.
• Collaborate with data scientists to integrate ML models.

Skills

ML Ops

Cloud Platforms (AWS, GCP, Azure)

Scripting (Python, Bash)

Monitoring Tools (Prometheus, Grafana)

Automation

Collaboration

Continuous Learning

Education

Bachelor’s degree in Computer Science

Master’s degree in Data Engineering

Tools

Docker

Kubernetes

Terraform

Ansible

Git

Job description

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I build Data and Machine Learning teams for the best companies in Australia | Nuage Technology Group

The Role

Nuage has partnered with a dynamic scale-up to recruit a talented ML Ops Engineer. In this role, you will be instrumental in building and maintaining the infrastructure that supports machine learning models at scale. This is a unique opportunity to contribute to transformative technology that will drive the company's growth and innovation.

Responsibilities

• Design, implement, and maintain scalable ML infrastructure.
• Automate the deployment and monitoring of ML models.
• Ensure the reliability and performance of ML systems in production.
• Collaborate with data scientists and engineers to integrate ML models into applications.
• Develop and maintain CI/CD pipelines for ML projects.
• Monitor and troubleshoot production ML systems.
• Optimize resource usage and cost-efficiency of ML infrastructure.
• Stay updated with advancements in ML Ops and cloud technologies.
• Document processes and best practices.
• Provide training and support to team members on ML Ops tools and practices.

Your Background

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Machine Learning, or a related field.
• 4-5 years of experience in ML Ops or related roles.
• Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization (e.g., Docker, Kubernetes).
• Proficiency in scripting and automation (e.g., Python, Bash).
• Strong understanding of ML lifecycle and deployment strategies.
• Experience with monitoring and logging tools (e.g., Prometheus, Grafana).

Preferred Skills

• Familiarity with ML frameworks (e.g., TensorFlow, PyTorch).
• Experience with infrastructure as code (e.g., Terraform, Ansible).
• Strong software engineering skills, including version control (Git) and collaborative workflows.
• Prior experience working in a collaborative, fast-paced team.
• Strong communication skills, both written and verbal.
• Willingness to engage in continuous learning and professional development.

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Information Technology

Industries

Technology, Information and Media