Senior AI Infrastructure Engineer

Our client is scaling its cutting-edge AI capabilities and is looking for a highly experienced Senior AI Infrastructure Engineer for a fully remote role. You will be responsible for designing, building, and maintaining the robust, scalable, and efficient infrastructure that powers our AI and machine learning workloads. This includes managing compute resources, storage, networking, and deployment pipelines essential for AI model training and inference.

As a remote-first team member, you will collaborate with a global team of engineers, data scientists, and researchers, ensuring the seamless operation and continuous improvement of our AI platform. Your expertise will be critical in enabling rapid innovation and deployment of AI solutions.

• Design, deploy, and manage scalable and reliable infrastructure for AI/ML workloads (e.g., GPU clusters, distributed storage).
• Optimize infrastructure performance for large-scale model training and inference.
• Implement and manage CI/CD pipelines for ML models and infrastructure as code.
• Develop and maintain monitoring, logging, and alerting systems for AI infrastructure.
• Automate infrastructure provisioning, configuration, and management using tools like Terraform or Ansible.
• Ensure the security and compliance of the AI infrastructure.
• Collaborate with AI/ML engineers and data scientists to understand their infrastructure needs and provide support.
• Troubleshoot and resolve complex infrastructure issues in a timely manner.
• Stay current with the latest trends in cloud computing, containerization (Docker, Kubernetes), and AI infrastructure.
• Contribute to the architectural decisions and technical roadmap for AI infrastructure.

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Proven experience (5+ years) in infrastructure engineering, with a strong focus on AI/ML platforms.
• Expertise in cloud platforms (AWS, Azure, GCP) and their relevant services (e.g., EC2, S3, EKS/AKS/GKE).
• Strong experience with containerization technologies (Docker, Kubernetes).
• Proficiency in scripting languages (e.g., Python, Bash) and Infrastructure as Code (IaC) tools.
• Understanding of networking concepts and distributed systems.
• Experience with monitoring tools (e.g., Prometheus, Grafana) and logging frameworks.
• Familiarity with ML frameworks (Tensor Flow, PyTorch) and MLOps principles is a plus.
• Excellent problem-solving and debugging skills.
• Strong communication and collaboration abilities in a remote environment.

• Highly competitive salary and performance bonuses.
• Fully remote work flexibility.
• Comprehensive health, dental, and vision insurance.
• Generous stock options.
• Unlimited paid time off.
• Annual budget for learning and development (conferences, courses, books).
• Home office equipment allowance.
• Retirement savings plan with company contribution.