Remote Senior AI/ML Infrastructure Engineer

About the Role

Our client is a pioneering technology firm building the next generation of AI-powered products, and we are looking for a highly skilled Remote Senior AI/ML Infrastructure Engineer to join our distributed engineering team. This is a fully remote position focused on designing, building, and maintaining the robust, scalable infrastructure required to support our cutting-edge machine learning development and deployment. You will be instrumental in creating and optimizing the systems that enable our data scientists and ML engineers to efficiently train, evaluate, and deploy complex models. The ideal candidate has a deep understanding of MLOps principles, cloud infrastructure, and distributed systems, combined with a passion for enabling AI innovation.

Our client fosters a culture of collaboration, autonomy, and continuous improvement, providing an environment where your contributions have a direct impact. You will work with state-of-the-art technologies and collaborate with talented individuals from around the globe. We believe in empowering our engineers with the tools and infrastructure they need to succeed, making this role critical to our continued growth and success in the AI space. This is an opportunity to architect and implement the foundational systems that drive our AI initiatives forward.

Key Responsibilities

• Design, implement, and manage scalable and reliable ML infrastructure on cloud platforms (AWS, Azure, or GCP).
• Develop and maintain CI/CD pipelines for machine learning models and infrastructure.
• Build and manage data pipelines for large-scale ML datasets.
• Optimize compute resources for ML training and inference workloads.
• Implement monitoring, logging, and alerting for ML systems.
• Automate infrastructure provisioning and management using tools like Terraform or Ansible.
• Collaborate with ML engineers and data scientists to understand their infrastructure needs.
• Ensure the security and compliance of ML infrastructure.
• Troubleshoot and resolve infrastructure-related issues in a timely manner.
• Evaluate and adopt new technologies to improve ML infrastructure capabilities.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in infrastructure engineering, with a strong focus on AI/ML workloads.
• Proven experience with cloud platforms (AWS, Azure, GCP) and their managed ML services.
• Expertise in containerization technologies (Docker, Kubernetes).
• Strong knowledge of MLOps best practices and tools (e.g., MLflow, Kubeflow).
• Proficiency in scripting languages such as Python, Bash.
• Experience with infrastructure-as-code tools (e.g., Terraform).
• Solid understanding of networking, security, and system administration principles.
• Excellent problem-solving and debugging skills.
• Strong communication and collaboration skills, comfortable working in a remote team.

Benefits

Our client offers a competitive salary, performance bonuses, and comprehensive health, dental, and vision insurance. As a remote employee, you'll benefit from flexible working hours and generous paid time off. We provide resources for home office setup and professional development opportunities, including conferences and training. Join our innovative and collaborative team, driving the future of AI infrastructure from anywhere.