red hat openshift ai consultant
Budget: $250 – $750 USD
I am in the middle of an OpenShift AI roll-out and need hands-on expertise to move from proof-of-concept to a stable, production-ready environment.
The immediate focus is threefold:
• Building AI models that demonstrate clear business value
• Optimising the underlying OpenShift infrastructure for performance, scalability, and cost-efficiency
• Automating end-to-end workflows so that model training, testing, and deployment run reliably with minimal manual effort
Your experience across the OpenShift AI stack will be critical. If you already work with OpenShift Data Science, Pipelines, or the Service Mesh, that knowledge will slot straight into our roadmap.
Deliverables
1. A functioning model (or models) deployed on our OpenShift cluster, packaged for repeatable training and inference.
2. Infrastructure tuning recommendations applied and benchmarked, complete with before/after metrics.
3. A fully automated pipeline—from data ingestion to model promotion—documented and running inside our CI/CD process.
4. Clear hand-off documentation so the internal team can maintain and extend the solution.
We move fast, communicate openly, and value concise, well-commented work. If you can dive in and get tangible results on these fronts, let’s connect.
The immediate focus is threefold:
• Building AI models that demonstrate clear business value
• Optimising the underlying OpenShift infrastructure for performance, scalability, and cost-efficiency
• Automating end-to-end workflows so that model training, testing, and deployment run reliably with minimal manual effort
Your experience across the OpenShift AI stack will be critical. If you already work with OpenShift Data Science, Pipelines, or the Service Mesh, that knowledge will slot straight into our roadmap.
Deliverables
1. A functioning model (or models) deployed on our OpenShift cluster, packaged for repeatable training and inference.
2. Infrastructure tuning recommendations applied and benchmarked, complete with before/after metrics.
3. A fully automated pipeline—from data ingestion to model promotion—documented and running inside our CI/CD process.
4. Clear hand-off documentation so the internal team can maintain and extend the solution.
We move fast, communicate openly, and value concise, well-commented work. If you can dive in and get tangible results on these fronts, let’s connect.