Full Stack Software Engineer

Job description

Running a flexible Machine Learning engine at scale is hard. We must ingest and process large volumes of data uninterruptedly and store it in a scalable manner. The data needs to be prepared and served to hundreds of models constantly. All the predictions of the models, as well as other data pipelines, must be stored and reachable for our web application(s) to present the generated insights to our customers.

We work on the system that delivers this functionality and also allows the machine learning engineers to deliver new and improved models at ease, manage existing models, monitor these models, and many different interactions, all of which are crucial to day to day operations.

You will be working and interacting with a wide array of technologies that constitute Jungle's core systems (data handling/processing, serving ML models, etc...) and building the backend/frontend systems that provide access to all this functionality. You will have the possibility to work on and enhance the different stages of an end-to-end machine learning system at scale.



Who we are

Jungle develops and applies Artificial Intelligence to increase the uptime and performance of renewable energy sources. Built on existing sensors and data streams, the company’s technology enables solar and wind energy owners to squeeze more out of their assets, accelerating the world’s transition to renewable energy sources.


We have productised our services into a web application and are continuously improving it to ensure that our best analyses and visualisations help our users get the maximum energy out of their assets. We operate at a large scale - billions of data points per day - providing always-on predictive models, alarms and metrics visualisations for some of the largest and most sophisticated customers in the global renewable energy space. This is not your average dashboard, we’re talking about intelligently visualising handling large quantities of data to drive performant visualisations and functionality.


Why do we need you?

  • Make use of modern open-source technologies in a practical use case to improve usability, performance and robustness of our internal system.
  • Contribute to the creation of new backend and frontend components of a MLOps platform that enables data scientists to easily deploy models and other pipelines to production.
  • Work together with the engineering team to maintain and improve existing systems, and overcome difficulties arising from scaling up our systems to more and more data.
  • Make architectural decisions on how to solve our engineering challenges and keep us future proof.
  • Research new (upcoming) technologies that will considerably improve the user experience and or development time of our products.


Why work with us?

  • Join a funded start-up in the scaling phase.
  • You have the opportunity to use your skills to create a meaningful change in this world.
  • We care about your growth and assign you a personal mentor to help you achieve this.
  • As part of a small and experienced team, you can enjoy freedom in your work and be involved in different areas of a ML focused system
  • You will be working on features and components that will require you to learn and explore new technologies
  • We offer you a flexible work schedule, holiday policy, and work location. We are a remote-friendly company.
  • Modern work environment, tools and peripherals.
  • Become part of a warm and skilled group of people.

Requirements

Requirements

We are looking for a Software Engineer that has experience in Python backend development, and some experience in frontend development with standard technologies (Javascript, React, Vue, etc).

  • MSc degree in Computer Science or related field, or equivalent experience.
  • Demonstrable experience in writing and maintaining efficient Python backend software
  • Demonstrable experience with any market standard javascript frontend technology stack (Vue, React, Angular, ...)
  • Experience in agile environments and development workflows using git or similar tools, and CI/CD tools such as Gitlab CI or Jenkins.
  • [preferred] Experience with container/orchestration tools (Docker, etc.) and cloud orchestration and deployment ecosystems such as Kubernetes
  • [preferred] Familiarity with common Python backend frameworks (Django, FastAPI, Flask, or something similar)
  • [preferred] Experience data orchestration tools like Airflow, Argo, Prefect, etc...


About you

  • You are curious and won't stop searching until you find the answer.
  • You work meticulously. People around you trust your work results, rightly so.
  • You're pragmatic; you know when to trade off diving deep with quick fixes.
  • You are eligible to work in the European Union.