Neptune.ai is one of the most ambitious startups in Europe. Our goal is to become the collaboration standard for data scientists (like GitHub/GitLab). We believe that machine learning/AI is the type of technology that has the potential to change the world and we want to be a part of it!
Some of the things we do are fairly run-of-the-mill engineering work (REST, SQL, NoSQL), but often we do something quite rare! How many companies have implemented a fully-featured GoogleDocs-like real-time collaborative editor? Or a custom autoscaler for an in-cloud Kubernetes cluster?
We’re always hungry for more knowledge and constantly striving to be better.
Interested?
Responsibilities
As part of our team, you will:
- develop beautiful and highly usable UI components.
- cooperate closely with Product Manager, UX Designer and Backend engineers while iterating on new features. We promote short feedback loop and value everyone’s opinion.
- improve the overall user experience of our product by increasing the quality of the frontend.
- teach other developers and share your experience. We want to learn from each other.
- participate in choosing the tools we use. We’ll lean on your knowledge and expertise to select technologies.
- participate in defining our application’s architecture.
Our expectations
- You’re always hungry for more knowledge – learning new things is natural for you, you do it constantly.
- You are proficient in JavaScript and have solid experience with large scale single page applications.
- You have a broad knowledge of the general web landscape, architectures, trends, and emerging technologies.
- You have experience with TypeScript.
- You have practical knowledge of ReactJS and Redux or other state management system / library.
- You know how to build reusable and composable UI components.
- You know how to break down UX/UI design into UI components and/or decide which existing component perfectly fits the design.
- You can understand the code on the libraries’ level.
- You do not stop debugging code when you enter libraries code.
- You point out mistakes at both: UX/UI design and the system architecture design level.
- You perform an excellent code review.
- Knowledge of Machine Learning concepts would be awesome!