Tech Stack
AWSAzureCloudGoogle Cloud PlatformPythonPyTorchTensorflow
About the role
- Own the technical architecture of the platform – design, build, and maintain scalable infrastructure for ML, data processing, and product delivery.
- Translate business and clinical needs into elegant, performant, and compliant technology – from proof of concepts to production.
- Build and maintain robust data pipelines to handle video, audio, EMR data, and natural language inputs.
- Develop and fine-tune ML models that support real-time coaching, sentiment analysis, and personalized documentation.
- Lead full-stack product development for internal tools, clinician-facing apps, and workflow integrations (e.g., Epic, ambient AI platforms).
- Collaborate cross-functionally with clinicians, researchers, and design to create solutions that are both clinically effective and technically feasible.
- Drive experimentation, iteration, and validation – balancing speed with safety in healthcare-grade deployments.
- Implement best practices for data privacy, security, and compliance (e.g., HIPAA).
- Lead technical planning for clinical studies and research pilots (option to serve as PI if desired).
- Help build out and lead a high-performing engineering team as the company scales.
Requirements
- Experience with direct ownership over product, code architecture, or platform codebases.
- Deep fluency in Python, ML frameworks (e.g., PyTorch, TensorFlow), and production-grade backend systems.
- Experience building and deploying ML or AI-powered features in real-world applications (bonus if healthcare-related).
- Proficiency in designing scalable infrastructure on cloud platforms (e.g., AWS, GCP, Azure).
- Experience with audio, text, or multimodal data pipelines is a major plus.
- Comfortable operating in ambiguity and wearing multiple hats in a fast-moving startup environment.
- Care deeply about ethical AI and patient-centered technology.
- Prior startup or founding experience is a strong plus.
- Fluent English level.