Own projects end-to-end. Scope, architect, and ship full-stack AI/ML systems using Python (and any language that gets the job done). Build innovative solutions. Optimize and deploy state-of-the-art models, tune inference pipelines, and push the boundaries of performance, cost, and scale. Own customer relationships. Serve as the primary technical point-of-contact, guiding customers from prototype to production and ensuring long-term success. Act as a product manager in the field. Capture qualitative and quantitative feedback, synthesize themes, and translate them into clear product requirements that influence our roadmap. Publish and share your work. Write blog posts, open-source examples, and conference talks that expand what’s possible with AI inference.