Gcore
AI, cloud, network, and security
AISolutionArchitect
“AI Solution Architect at Gcore. Skills: GPU, Kubernetes, Terraform, Python. Design end-to-end GPU cluster architectures. Deploy large-scale GPU clusters”
What You'll Achieve.
ensure seamless, repeatable deployments; drive product enhancements
Industry & Context.
What They're Looking For.
Must Have
3+ years in Cloud or GPU AI Infrastructure DevOps, Proven track record deploying GPU clusters at scale, Hands-on with Ansible or similar configuration management Terraform (IaC), familiarity with Kubernetes (K8s) and Slurm, Proficient in Python / Go, Solid understanding of ML ecosystems, Excellent verbal and written ability
Nice to Have
Experience deploying high-availability inference infrastructure for production AI workloads, Implement and optimize distributed training and inference pipelines with MLflow, REST APIs, and popular frameworks (PyTorch, TensorFlow, JAX), Demonstrated ability to transition ML pipelines from proof-of-concept to robust, scalable production systems, Familiarity with GitOps workflows, Docker, Helm charts, and CI/CD for ML, Knowledge of Hugging Face transformers, Scikit-learn, and experiment tracking best practices
What You'll Do.
Design end-to-end GPU cluster architectures
Deploy large-scale GPU clusters
Design containerized training pipelines
Deploy production inference systems
Automate provisioning
Host webinars and training sessions
Relay customer insights
How You'll Work.
Team & Collaboration
Collaborate closely with clients; Partner with Gcore's engineering and product teams
Communication Scope
translate complex technical concepts for diverse audiences
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