Platform Engineer

Overview

• Lead the development and optimization of scalable Kubernetes platforms tailored for high-performance machine learning workloads.
• Design and deploy GPU-accelerated clusters across hybrid cloud and bare-metal infrastructures to support advanced computing needs.
• Implement robust CI/CD pipelines to streamline software delivery and enhance operational efficiency.
• Develop and maintain observability systems to monitor infrastructure performance and ensure reliability.
• Collaborate with cross-functional teams to refine development workflows and optimize tooling.
• Apply infrastructure-as-code practices to ensure consistency and scalability in system configurations.
• Manage core infrastructure components, including networking, storage, and system setups.
• Ensure compliance with security standards and implement measures to mitigate risks.

Key Responsibilities & Duties

• Deploy and manage Kubernetes clusters optimized for GPU-accelerated machine learning workloads.
• Enhance system performance through proactive monitoring and optimization strategies.
• Design and operate automated CI/CD pipelines to support efficient software delivery.
• Develop observability tools to monitor system health and generate actionable insights.
• Collaborate with development teams to refine tooling and improve deployment processes.
• Implement infrastructure-as-code using tools such as Terraform, Helm, and Ansible.
• Manage networking, storage, and system configurations for high-performance environments.
• Ensure adherence to stringent security standards and protocols.

Job Requirements

• Bachelor's degree in Computer Science or a related field is required.
• Minimum of 3 years, preferably 5 years, of experience in platform engineering or DevOps.
• Proficiency in Python and Bash for scripting and automation tasks.
• Strong expertise in Kubernetes administration and GPU environments.
• Experience with CI/CD pipeline design and observability tools.
• Advanced knowledge of Linux systems and infrastructure-as-code practices.
• Ability to manage complex systems and ensure compliance with security standards.
• Preferred experience with machine learning orchestration tools and build toolchains.