Yes, we're still hiring despite the pandemic!
We are looking for a driven, experienced engineer who is excited about our mission and wants to help us build a user-friendly application that improves the health of thousands of people around the world.
The role encompasses:
- Deepening the integration of our "Motion Coach" technology in our therapy apps
- Participating in product design and iteration with the cross-functional, self-managed team that owns the development of our Motion Tracking Platform (you will sit in a team of mobile, backend, ML/CV engineers, sport scientist, PM, designers, etc.)
- Further developing our medical device API and admin interface in Ruby on Rails by defining and iterating on software architecture.
- Implementing new features, selecting frameworks and libraries, scaling the platform to support a growing number of users, and maintaining cloud infrastructure.
- The opportunity to personally grow, get in touch with cutting edge ML/CV research (we build all vision models in house and push the SOTA in Pose Estimation on mobile) and learn with a team that pushes for productization of ML tech to solve a real problem with broad applicability
- Optional: Contribute to and drive forward our ML Data Platform and Python Django ML Macroservice
- You are a strong coder with deep technical knowledge of backend development using Ruby on Rails
- Strong software architecture & data modelling skills and ability to base engineering decisions on product vision
- Strong knowledge of data structures, design patterns, and software engineering best practices
- Strong engineering background, preferably with academic training in Computer Science, Software Engineering, or equivalent practical experience
- Willingness and ability to work in a cross-functional, product-focused team, and actively participate in the design of future features and iterations
Ideally you also have (completely optional):
- Understanding of machine learning concepts or first practical experience
- Initial working experience with Python
- DevOps experience using Docker, Terraform, Elastic Beanstalk, Kubernetes