ML Platform / DevOps Engineer

Metacognition; Australia; Remote; AUD 130,000 - 190,000; Full time

Benefits offered by this job

Remote working

Job summary

Metacognition is seeking an ML Platform / DevOps Engineer to design, secure and maintain cloud infrastructure for large-scale AI training, inference and evaluation platforms. You will enable research and engineering teams with automated environments, scalable pipelines and governance to ship software rapidly and safely.

Role scope aligns with candidate experience, offering a hands-on blend of software engineering and cloud operations across development and production environments.

Qualifications

• Proven experience in ML platform engineering and DevOps.
• Experience running ML training/serving at scale.
• Expertise with GitHub and GitHub Actions for CI/CD.

Responsibilities

• Build and automate development environments for AI, data and app development.
• Design and implement CI/CD pipelines and deployment patterns (GitHub Actions).
• Develop reusable infra templates and automation for rapid environment creation.
• Establish access controls, governance and guardrails across environments.
• Integrate GitHub with cloud services and supporting platforms.
• Embed security, compliance and operational controls into platform delivery.
• Create reusable platform components adopted across teams.

Skills

ML platform engineering

DevOps

GitHub Actions

Cloud platforms (AWS/GCP)

Infrastructure as Code (Terraform, Pul

Tools

GitHub

Terraform

Pulumi

Kubernetes

Job description

Role Overview

The ML Platform / DevOps Engineer will develop, secure and maintain cloud infrastructure and enable large-scale training, inference and evaluation platforms. Supporting the research and engineering teams by developing environments and automation pipelines necessary for teams to rapidly prototype, perform research, and continuous shipping of software. This role combines strong software engineering with hands-on cloud and DevOps experience and willingness to enable teams to move quickly while maintaining the security, governance and operational foundations needed to operate reliably at scale.

Role scope will be calibrated to the experience and profile of the candidate.

Key Responsibilities

Engineering

• Build and automate development environments that allow teams to safely experiment with AI, data and application development.

• Design and implement CI/CD pipelines and deployment patterns, particularly using GitHub and GitHub Actions.

• Develop reusable infrastructure templates, provisioning workflows and automation for rapid and consistent environment creation.

• Establish environment access controls, governance and operational guardrails across development and production environments.

• Build and maintain integrations between GitHub, cloud services and supporting technology platforms.

• Establish DevSecOps practices, embedding appropriate security, compliance and operational controls into platform delivery.

• Develop standards and reusable patterns that can be adopted across multiple development teams.

Collaboration

• Work with engineering and research teams to onboard testing environments; streamline release and provide compute and data scaling for on-going and ad-hoc research projects.

• Advise development teams on platform architecture, deployment, scalability, operational support and long-term maintainability.

• Improve developer workflows and establish practices that enable teams to move rapidly from experimentation through to production.

• Contribute to a rigorous and supportive engineering culture, sharing knowledge and helping establish effective platform engineering practices.

Essential

• Strong experience in ML platform engineering, DevOps.

• Strong experience working with AI/ML platforms at scale (training/serving).

• Strong experience with GitHub and GitHub Actions, including CI/CD and automated deployment.

• Hands-on experience with cloud platforms, ideally AWS or GCP.

• Experience with Infrastructure as Code and infrastructure automation (i.e. Terraform, Pulumi).

• Experience designing and automating development environments, deployment workflows and cloud infrastructure.

• Solid understanding of cloud security, governance, and role-based access controls.

• Experience with containers and Kubernetes-based environments.

• Experience building internal developer platforms, self-service infrastructure or reusable platform capabilities.

• Strong software engineering skills and an understanding of the developer journey from development and experimentation through production.

Preferred

• Familiarity with deploying and integrating agentic workflows into supporting platforms to accelerate company knowledge sharing and processes (github, aws, glean, slack, linear)

• Experience establishing DevSecOps practices across cloud and application environments.

• Experience designing platforms that support the transition of AI and data prototypes into production services.

• Familiarity with modern cloud-native development and observability practices.

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Why join Metacognition?

You’ll work alongside leading researchers, engineers and thinkers to build intelligent systems capable of learning, remembering and reasoning over time. We're an early stage startup with ambitious goals. Joining us will give you a genuine opportunity to shape both our technology and the company we become.

What you can expect

• Competitive remuneration

• Remote working

• The opportunity to work with leading researchers, engineers and industry experts

• A highly collaborative, fast-moving environment

• Meaningful ownership and the opportunity to influence how we build and grow

• Opportunities to learn, experiment and work on genuinely challenging problems

Metacognition is committed to creating an inclusive workplace where different perspectives, experiences and backgrounds are valued. We encourage applications from people with diverse backgrounds and experiences.

Interested?

If you’re excited by ambitious problems, intelligent systems and the opportunity to build something from the ground up, we’d love to hear from you.