Full-Stack Developer for ML Platform
Budget: $750 – $1,500 USD
I’m kicking off a green-field project and need a seasoned full stack developer to build a new application that will sit on top of an existing Machine Learning Platform. You’ll own the end-to-end stack—from shaping database schemas and REST/GraphQL APIs to crafting a clean, responsive UI—while collaborating with me entirely remotely.
Strong, clear English is essential because we’ll sync frequently over video to refine requirements, review code, and iterate quickly. I value proactive communication: if something is unclear, I expect you to ask rather than guess.
Tech choices are flexible, but I’m currently leaning toward Python (FastAPI or Django) or Node.js for the back end and React or Vue on the front end. Experience containerising services (Docker, Kubernetes), wiring up CI/CD pipelines, and integrating with ML inference endpoints will help you hit the ground running.
Key deliverables:
• A working MVP deployed to a staging environment
• Source-controlled, well-documented code with unit and integration tests
• Deployment scripts and concise hand-off documentation so I can spin up the stack in one command
If you thrive on building applications from scratch, are comfortable navigating both front- and back-end challenges, and can articulate complex ideas in plain English, let’s talk.
Please include the following when applying:
1. A short video or audio introduction (1–2 minutes) describing your background and experience.
2. A GitHub link or samples of recent software projects.
3. Confirmation that you are comfortable with client video interviews in English.
Strong, clear English is essential because we’ll sync frequently over video to refine requirements, review code, and iterate quickly. I value proactive communication: if something is unclear, I expect you to ask rather than guess.
Tech choices are flexible, but I’m currently leaning toward Python (FastAPI or Django) or Node.js for the back end and React or Vue on the front end. Experience containerising services (Docker, Kubernetes), wiring up CI/CD pipelines, and integrating with ML inference endpoints will help you hit the ground running.
Key deliverables:
• A working MVP deployed to a staging environment
• Source-controlled, well-documented code with unit and integration tests
• Deployment scripts and concise hand-off documentation so I can spin up the stack in one command
If you thrive on building applications from scratch, are comfortable navigating both front- and back-end challenges, and can articulate complex ideas in plain English, let’s talk.
Please include the following when applying:
1. A short video or audio introduction (1–2 minutes) describing your background and experience.
2. A GitHub link or samples of recent software projects.
3. Confirmation that you are comfortable with client video interviews in English.