AI/ML Sprint: 2-Hour End-to-End Build & Audit

This 120-minute engagement is a high-touch, hands-on sprint with a senior AI/ML engineer who has delivered production-ready generative-AI, voice, and vision systems across multi-GPU cloud clusters.

What we can accomplish together:

• Architecture & Design – Jointly architect or refactor your entire ML pipeline (data ingestion → model training → CI/CD → scalable Kubernetes deployment).
• Live Code Review & Pair-Programming – Walk through critical codebases to surface bugs, bottlenecks, and security gaps, implementing fixes in real time.
• Performance Tuning – Apply pruning, quantization, and distributed-training best practices to cut inference latency and cloud costs.
• RAG & LLM Workflow Optimization – Redesign retrieval, embedding, and memory strategies for higher accuracy and faster responses.
• Go-Live Checklist – Produce a deployment playbook covering monitoring, rollback, and cost-control measures.

You’ll leave with:

• A revised architecture diagram and prioritized action plan.
• On-session code commits or pull-request drafts.
• A curated resource list (repos, docs, infra blueprints) to sustain momentum.

Ideal for teams prepping a launch, tackling complex scaling issues, or needing an expert audit before significant investment.