I’m at the idea stage of a machine-learning–driven application and need a seasoned, CTO-level partner who can own the technical side from day one. What I’m looking for • Shape the technical strategy and high-level architecture, making sure it can scale as the product matures. • Stay hands-on: write the first lines of production-ready code, set up repos, CI/CD, and deploy an initial proof-of-concept or MVP. • Guide early hiring decisions once we’re ready to build a wider engineering team. Tech stack I’m open to your recommendations. Whether that’s Python with TensorFlow/PyTorch, a cloud-native approach on AWS, GCP, or Azure, or even low-latency options in another language, I want to leverage whichever tools best fit the problem and timeline. Deliverables (first 4–6 weeks) 1. A concise technical roadmap outlining phases, risks, and resource needs. 2. A documented architecture diagram and decision log. 3. A functional prototype or skeleton service that demonstrates the core ML workflow (data ingest, training, and inference pipeline). 4. Deployment scripts or containerization for easy hand-off and future scaling. If you thrive in zero-to-one environments, enjoy shaping product strategy with founders, and can both think big and code small, let’s talk.