Platform Engineer

We are seeking a talented and passionate Platform Engineer with a strong focus on MLOps to join our innovative remote team, based in Sydney, Australia. In this crucial role, you will be instrumental in designing, building, and maintaining robust, scalable, and secure machine learning platforms that empower our data science and engineering teams. You'll work at the intersection of infrastructure, data, and machine learning, ensuring our ML models can be developed, deployed, and managed efficiently from experimentation to production.

You will play a key role in evolving our cloud-native ML platform, leveraging cutting-edge technologies to streamline the entire MLOps lifecycle. This is an exciting opportunity for an individual who thrives on solving complex infrastructure challenges, has a deep understanding of cloud environments, and is passionate about enabling data-driven innovation.

• Design and implement scalable and reliable MLOps pipelines using tools like Kubeflow, MLflow, and Apache Airflow.
• Manage and optimize Kubernetes clusters and associated infrastructure on AWS, ensuring high availability and performance for ML workloads.
• Develop and maintain Infrastructure as Code (IaC) using Terraform to provision and manage cloud resources efficiently.
• Build and support CI/CD pipelines (e.g., GitLab CI, GitHub Actions) for automated model training, testing, and deployment.
• Collaborate closely with data scientists and machine learning engineers to understand their needs and provide expert guidance on best practices for ML model lifecycle management.
• Monitor, troubleshoot, and optimize the performance and cost-efficiency of our ML platform components.
• Champion best practices in security, reliability, and observability across the ML infrastructure.

Required Skills & Tools: Expertise in cloud platforms (AWS strongly preferred), Kubernetes, Docker, Terraform, CI/CD methodologies, Python, and Linux. Demonstrated experience with MLOps tools such as Kubeflow, MLflow, or similar. Strong understanding of data engineering principles and distributed systems.

Nice-to-Have: Experience with other cloud providers (GCP, Azure), knowledge of data warehousing solutions (e.g., Snowflake, Redshift), proficiency with monitoring tools (Prometheus, Grafana), or prior experience in a high-growth tech environment.

What We Offer: A dynamic and supportive remote work environment with a focus on collaboration and continuous learning. Competitive salary commensurate with experience (USD 110,000 – 145,000 / year). Opportunities for professional development and growth. Flexible working hours and a culture that values work-life balance. Access to cutting-edge technologies and the chance to make a significant impact on our product and platform.