Product Strategy, Backlog & Sprint Planning for Startups
Starting at: €250.00
Production ML & MLOps Implementation
14 Views
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Basic Delivery Time21 Days
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Experience (Years)7
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What You GetI deliver a containerised model with a production-ready Dockerfile and serving config (TensorFlow Se, I set up a CI/CD pipeline (training → test → deploy) integrated with GitHub Actions for automated, r, I provide monitoring, alerting and a dashboard for data drift, performance regressions and latency., I configure an MLflow registry with versioned artifacts and documented rollback procedures.
Service Description
I build reproducible, production-ready ML systems: containerised models, CI/CD for model training/deployment, monitoring and rollback. Includes Docker/Kubernetes, TensorFlow Serving or TorchServe, model registry (MLflow), GitHub Actions and basic infra-as-code for AWS/GCP. Ideal for teams moving prototypes into 24/7 production with observability and automated retraining.
What's Included:
• Containerised model + Dockerfile
• CI/CD pipeline (training → test → deploy)
• Monitoring & basic alerting
• Model registry and versioning setup
• Deployment handover docs
