What You'll Do- Design, build, and ship high-quality product experiences: Own key surfaces and services end to end, from concept through production. Write elegant, well-tested code that makes complex clinical and operational behavior feel simple and reliable.
- Work AI-first with Cursor and Claude Code: Use LLMs, Cursor, and Claude Code as your starting point. Draft intent, explore implementations, scaffold components, and refactor with AI in the loop. Apply your own judgment to meet the quality bar healthcare demands.
- Prototype fast and validate with real users: Build and test implementations quickly with real patients and care teams. Use what you learn to refine before fully committing - especially in sensitive clinical contexts where getting it right matters.
- Build for scale and own the codebase: Translate product needs into reusable, well-architected patterns. Build in a way that makes the next feature faster to ship and easier to maintain.
- Make automation legible and trustworthy: Build systems that clearly communicate what AI and automation are doing on behalf of patients and providers. Earn trust through transparency, reliability, and thoughtful defaults.
- Champion performance, accessibility, and reliability: Ship work that is fast, robust, and accessible. Partner across the team to debug, optimize, and raise the bar over time.
- Share AI-native workflows: Document prompts, patterns, and workflows that work. Share them across the engineering team so we move faster together without cutting corners that matter to patient outcomes.
RequirementsWe are looking for a skilled Machine Learning Engineer to become a key player on our team. The successful candidate will be passionate about crafting sophisticated machine learning models and AI-powered solutions. In this role, you'll tackle a diverse range of projects, and work closely with cross-functional teams to seamlessly integrate AI into our products and services.
Qualifications:
- Bachelor's degree in Computer Science, Engineering, Mathematics, or related STEM field.
- 3+ years of professional experience in machine learning or computer vision.
- Strong programming skills in Python and experience with TensorFlow (PyTorch a plus).
- Hands-on experience building ML pipelines and working with distributed data processing frameworks like Apache Spark, Databricks, or similar.
- Cloud experience (AWS, Azure, or GCP), including building, deploying, and optimizing solutions with ECS, EKS, or AWS Lambda.
- Excellent problem-solving skills and ability to work in a collaborative environment.
Benefits 
