Full-Stack Engineer, Deep Learning
Butterfly Network’s mission is to democratize healthcare by making medical imaging accessible to everyone around the world. We are reinventing medical imaging and championing a new era of healthcare by creating the first ever pocket-sized, whole-body ultrasound device - the Butterfly iQ. This breakthrough technology has reduced the cost of the traditional ultrasound system by miniaturizing it onto a single semiconductor silicon chip.
Since inception, Butterfly has raised over $375 million. The iQ is FDA-cleared and is being sold in hospitals and clinics around the globe.
Joining Butterfly Network is the opportunity to redesign the future of healthcare through the power of technology. Embark on a journey with us to maximize global impact, motivated by the idea that our products will change the lives of millions along with the people you love.
To build machine learning algorithms solving clinical problems, Butterfly’s Deep Learning team needs to create and analyze large-scale image datasets, collect annotations from clinical experts, and evaluate model performance. To this end, the Butterfly’s Deep Learning team relies heavily on an internal Cloud-based solution that enables efficient medical image annotation, data curation, analytics and interpretation of medical machine learning algorithms. Your role would be to take ownership over this system and help it grow and mature. You will work closely with other members of the deep learning team to understand their needs, develop the technical roadmap necessary for achieving it, and be primarily responsible for its implementation.
As part of our team, your core responsibilities will be:
- Own and expand our Cloud-based solution that enables a host of doctors and sonographers to be assigned and complete annotation tasks: the foundation of all of our Deep Learning algorithms.
- Work closely with the Deep Learning team to translate their machine learning annotation requirements into GUI-based tools for annotation of Ultrasound images.
- Develop tooling and dashboards for research scientists and clinical program managers to curate and monitor large-scale datasets.
- Create visualization and evaluation tools and workflows that help research scientists to both evaluate machine learning models in development as well as analyze and monitor performance in the field.
- 4+ years of experience in full-stack web development, especially using React, Node.js
- A track record of owning business problems and leading developers to deliver effective solutions in a modern, cloud-based architecture
- Bachelor's Degree in Computer Science or equivalent experience
Ideally, you also have these skills/experiences/attributes (but it’s ok if you don’t!):
- Familiarity with server-side Python libraries such as Django or Flask
- Designing elastic and resilient distributed systems in a cloud environment such as AWS, GCP, or Azure
- GraphQL and related frameworks e.g. Relay, Apollo and URQL
- Containerization and orchestration technologies such as Docker, Kubernetes, ECS, EKS
- SQL (especially modern versions of PostgreSQL)
We offer great perks:
- Fully covered medical insurance plan, and dental & vision coverage - as a health-tech company, we place great worth on our teams’ well-being
- Competitive salaried compensation - we value our employees and show it
- Equity - we want every employee to be a stakeholder
- Pre-tax commuter benefits - we make your commute more reasonable
- Free onsite meals + kitchen stocked with snacks.
- 401k plan - we facilitate your retirement goals
- Beautiful office overlooking the Flatiron building in NYC
- The opportunity to build a revolutionary healthcare product and save millions of lives!
For this role, we provide visa assistance for qualified candidates.
Butterfly network does not accept agency resumes.
Butterfly Network Inc. is an E-Verify Company and is an equal opportunity employer regardless of race, color, ancestry, religion, gender, national origin, sexual orientation, age, citizenship, marital status, disability or Veteran status. All your information will be kept confidential according to EEO guidelines.