Note: The job is a remote job and is open to candidates in USA. GMI Cloud is an AI-native infrastructure company delivering GPU compute, inference services, and infrastructure for AI agents. The Infrastructure Backend Engineering Development Engineer will design, build, and maintain scalable AI/ML infrastructure, including resource provisioning, workload scheduling, observability, security, and GPU cluster operations.
Responsibilities
- Design, implement, and maintain AI/ML infrastructure optimized for large-scale training and inference
- Develop automation pipelines for GPU/CPU resource provisioning and workload scheduling using DevOps best practices and methodologies
- Develop observability and telemetry solutions to pro-actively monitor hardware performance, utilization, and health to ensure cluster reliability and efficiency
- Optimize infrastructure for high-throughput data transfer and low-latency communication
- Manage infrastructure security, access controls, and compliance standards for on-prem GPU cluster environments
- Collaborate with relevant engineering teams to configure and troubleshoot GPU clusters and hardware resources
- Document infrastructure architecture, deployment procedures, automation workflow, and operational best practices
- Stay current with the latest GPU technology developments, infrastructure engineering and integrate new hardware/software solutions as appropriate
Skills
- Bachelor's degree in Computer Science or related field
- Proficiency in at least one programming language (Golang, Python, Bash) with strong coding practices and system design skills
- Extensive experience with infrastructure orchestration platforms, especially OpenStack and Kubernetes
- Strong proficiency in automation, configuration management, and CI/CD pipelines using Ansible, Jenkins, GitLab CI, or similar
- Proven experience implementing telemetry and observability solutions (e.g. Prometheus, Grafana, Mimir and related technologies)
- Knowledge of networking, security, and performance tuning in GPU clusters
- Hands-on experience in deploying GPU clusters and managing GPU workloads
- Experience with secret management using HashiCorp Vault
- Experience with distributed and high performance storage systems (e.g. Vastdata, Weka, DDN, Ceph)
- Strong system thinking and abstraction skills, capable of designing complex distributed systems from an end-to-end perspective
- Strong understanding of DevOps principles, automation, and cloud-native architectures
- Meeting every qualification is not required
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