AI Backend Model Fine-Tuning Engineer

I’m looking for a backend-savvy AIML engineer who can jump straight into an existing codebase, fine-tune our current model, and expose it through lightweight, API-driven endpoints. You’ll be the point person for evaluating deliveries from other teams, running your own tests, and proposing pragmatic optimizations that keep inference fast and resource-efficient.

What I need you to do:
• Audit the current model and data pipeline, identify quick-win tweaks, then carry out fine-tuning to improve accuracy and latency.
• Wrap the refined model in clean REST/GraphQL endpoints so our product team can consume predictions with minimal friction.
• Design a simple test harness to validate each build and spotlight regressions before they hit production.
• Document your approach and rationale so future iterations are easy to pick up.

You’ll have plenty of autonomy, so I value engineers who bring ideas forward instead of waiting for step-by-step specs. Include a brief, focused proposal outlining your plan for the first milestone, any tools you prefer (TensorFlow, PyTorch, Keras—open to what suits the task), and past wins that show you can deliver quickly on a modest hourly budget.

If that sounds like your style, let’s talk and get this model into top shape.