As a full stack Web Developer, you will drive the development of our core user-facing application and help us define the product vision. You will have the opportunity to take complete ownership of major aspects of our product. We will trust you to solve our most difficult challenges and empower you to constantly learn about better ways of serving our customers. Finally, you will have an outsized impact of defining not only the technical roadmap but the entire culture of the company.
Our tech stack consists of a ReactJS (including d3.js graph rendering) + Python Flask + MongoDB web app served across multiple Docker containers on AWS. The backend is powered by our patent-pending machine learning algorithms that have been developed over the course of 4 years. Your mission
What you need to succeed
- Build an exquisite web-based product that delivers massive value
- Improve our existing technical foundations, and influence our technical direction and strategy.
- Work closely with our customers to build the right product that lets them succeed.
- Be a great person and set the tone for everyone on the team!
- 3+ years of professional development experience with ReactJS
- Production Python experience, and at least one modern framework (flask, Django, Tornado, FastAPI, etc) + docker is nice to have.
- Experience in producing and consuming RESTful APIs.
- Experience with highly interactive or data-intensive web applications (e.g. D3.js)
- Experience with at least one major cloud provider (AWS, GCP, Azure)
- The ability to work in an unstructured, self-directed environment.
- A love for building, especially novel product experiences.
- Care and empathy for users. We fall in love with our users, not our products.
- Ability to communicate clearly and succinctly. Experience with Computer vision is a bonus.
Our tech stack consists of a ReactJS (including d3.js graph rendering) + Python Flask + MongoDB web app served across multiple Docker containers on AWS. Some of our current challenges include:
- processing efficiently and visualising intuitively vast amounts of data;
- supporting deployments across different infrastructures.
- engineering creative ways to integrate hooks that ingest data from different ML infrastructures and architectures.