AI/ML-focused software development
Support for biotech software and data workflows—from an early technical question to a maintainable implementation.
- Problem and data framingClarify the decision, available data, constraints, and useful measures of performance.
- Model and prototype developmentExplore analytical approaches and turn promising directions into testable software.
- Scientific data workflowsDesign reproducible pipelines for research, analysis, and operational use.
- Engineering and deployment planningConsider architecture, testing, traceability, monitoring, and cloud delivery from the outset.
Work can involve Python, R, TensorFlow, PyTorch, AWS, and GCP where they fit the project—not as a prescribed stack.