Infrastructure Engineer, Galaxy

• 10+ years of experience in infrastructure, platform, or systems engineering
• Deep, hands-on experience with Kubernetes in production
• Strong background in MLOps and ML platform operations
• Experience across DevOps, CI/CD, and cloud infrastructure (AWS, GCP, or Azure)
• Proven ability to design secure, enterprise-grade systems
• Proficiency in Go, Python, Java, or similar.

Desirable

• We are looking for a senior infrastructure leader who has designed and operated modern ML platforms at scale and understands the operational, security, and reliability challenges of real-world AI systems
• This role sits at the intersection of infrastructure engineering, MLOps, DevOps, and security, with a mandate to build systems that are fast for developers, safe for the business, and resilient in production
• Architect and own the core infrastructure for AI and ML workloads, including training, inference, experimentation, and evaluation
• Design and operate Kubernetes-based platforms for scalable, reliable, and cost-efficient AI workloads
• Build and evolve MLOps pipelines: model training, versioning, deployment, monitoring, rollback, and lifecycle management
• Establish best practices for DevOps and CI/CD across data, ML, and application layers
• Lead security and compliance for AI systems: secrets management, access controls, isolation, auditability, and supply-chain security
• Ensure high availability, observability, and incident response for production AI services
• Partner closely with ML engineers, researchers, and application teams
• Set technical direction, review designs, and mentor engineers