Healthcare AI/ML Pipeline Development

I’m building a new machine-learning workflow for a healthcare product and need a seasoned engineer who can own the entire pipeline. The project spans three core areas: • Data analysis & preprocessing – You’ll shape raw clinical and sensor data into clean, feature-rich datasets, handling typical healthcare quirks such as missing values, class imbalance, and PHI masking. • Model building & training – From classic scikit-learn baselines to deep-learning architectures in TensorFlow or PyTorch, I’ll rely on you to select, tune, and rigorously validate models against our key performance metrics. • Deployment & maintenance – Once we hit target accuracy, the model must ship to production. Expect containerised deployment (Docker/Kubernetes), CI/CD, automated monitoring, and periodic retraining hooks on AWS. Because the data touches protected health information, you should already be comfortable with privacy-first coding practices and understand the spirit of HIPAA compliance. I’m in the US Central Time zone and collaborate live, so solid spoken English and the ability to sync a few hours each weekday are essential. There’s no hard deadline—I prefer deliberate, well-documented progress over rushed output—but we’ll still agree on milestones to keep momentum. If you’ve previously delivered end-to-end ML systems in healthcare and enjoy iterating openly in CST hours, let’s discuss your approach and toolset.

Project ID: 40412220