I’m planning an end-to-end AI initiative and need an engineer who can jump in early, help clarify the problem statement, and then carry the solution through prototyping, testing, and deployment. The exact domain—whether classic machine learning, natural language processing, or computer vision—will be finalized after our first discovery session, so breadth of experience is a big plus. Here’s what I expect once we settle on the use-case: • A concise technical roadmap showing data requirements, model architecture choices (e.g., TensorFlow or PyTorch), and deployment strategy (cloud or on-prem). • A working prototype with clean, well-commented Python code. • Performance benchmarks and an explanation of trade-offs made. • Packaging for production, preferably via Docker and a REST or gRPC API, along with basic monitoring hooks. • Clear documentation so my internal team can maintain and extend the solution. If you have shipped AI systems before, can communicate complex ideas simply, and are comfortable iterating with tight feedback loops, let’s talk about timelines and milestones.