Senior AI Python Backend Developer
Budget / Salary$250–750
TypeFreelance project
LocationRemote
Posted57 minutes ago
I’m ready to hand over the core of our new AI-driven web platform to a senior-level Python specialist who can own the backend from architecture to deployment. The codebase will revolve around a modern Python framework—Django, FastAPI, or whichever stack you can defend for speed, maintainability, and clean dependency management—and you’ll wire in production-grade AI models that power real-time features such as conversational agents, analytics, recommendation engines, or computer-vision workflows as the product roadmap unfolds.
Here’s what success looks like: you design a scalable service layer, build and expose secure REST/GraphQL endpoints, weave in AI/ML pipelines built on libraries like PyTorch, TensorFlow, or scikit-learn, and automate tests and CI/CD so releases ship reliably. I’m expecting thoughtful database choices, caching, logging, monitoring, and a strategy for horizontal scaling once traffic spikes.
Within our first milestones you will
• deliver an architectural plan with tech justifications,
• stand up the initial backend modules with unit and integration tests,
• integrate at least one production-ready AI model end-to-end,
• document everything clearly so additional engineers can ramp up fast.
If you have a portfolio of AI-powered web products, performance benchmarks you’re proud of, and the habit of writing clean, well-commented code, let’s talk.
Here’s what success looks like: you design a scalable service layer, build and expose secure REST/GraphQL endpoints, weave in AI/ML pipelines built on libraries like PyTorch, TensorFlow, or scikit-learn, and automate tests and CI/CD so releases ship reliably. I’m expecting thoughtful database choices, caching, logging, monitoring, and a strategy for horizontal scaling once traffic spikes.
Within our first milestones you will
• deliver an architectural plan with tech justifications,
• stand up the initial backend modules with unit and integration tests,
• integrate at least one production-ready AI model end-to-end,
• document everything clearly so additional engineers can ramp up fast.
If you have a portfolio of AI-powered web products, performance benchmarks you’re proud of, and the habit of writing clean, well-commented code, let’s talk.
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