Dyania Health

Machine Learning Engineer

• Design, implement, and deploy ML-powered software components within a microservice architecture.
• Lead development and productionization of NLP and transformer-based models for biomedical information processing.
• Own the full ML lifecycle: data preparation, model training, evaluation, optimization, deployment, and inference at scale.
• Architect scalable and maintainable ML infrastructure and services.
• Collaborate cross-functionally with product, UX, and clinical stakeholders to understand requirements and rapidly prototype new capabilities.
• Analyze model and system performance; communicate findings and trade-offs clearly to technical and non-technical stakeholders.
• Ensure reliability, scalability, and security of ML services in production environments.
• Mentor junior engineers and contribute to raising the technical bar across the team.
• Contribute to architectural discussions and strategic technical decisions.
• Champion engineering best practices including testing, CI/CD, version control, and documentation.

Senior Machine Learning Engineer