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 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, with a focus on the initial steps of the entire pipeline: data ingestion.
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 - millions 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?
- You’ll make use of modern open-source technologies in a practical use case to improve usability, performance and robustness of our internal systems.
- You’ll 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.
- You’ll make architectural decisions on how to solve our engineering challenges and keep us future proof.
- You’ll integrate new systems with our existing data pipeline, with a focus on data ingress.
Why work with us?
- Join a funded scale-up.
- Work with modern technologies (both in ML and software engineering).
- You'll work on the last-mile delivery of our products, ensuring they have the best impact with our customers.
- You have the opportunity to use your skills to create a meaningful change in this world.
- Become part of a warm and skilled group of people, committed to each others success.
- We care about your growth and assign you a personal mentor to help you achieve this.
- As a remote-first company, we offer you a flexible work schedule, holiday policy, and work location.
- Demonstrable experience (2+ years) in software development, computer algorithms, data structures and statistics.
- You have experience with Python, including knowing what it's great at and when it's time to search for a different tool.
- You have contributed to the development and maintenance of backend technologies (FastAPI) and internal tooling that are running in production.
- You have some knowledge of distributed systems and computer networking.
- You are experienced with Docker and containers and benefit from their usage on your day to day activities.
- You have a firm knowledge of Linux-based systems (or similar), ideally in a server/headless environment, wielding your shell as a weapon that imposes fear on GUI users.
- Experience in agile environments and development workflows using git or similar tools, and CI/CD tools such as Gitlab CI or Jenkins.
Preferred Requirements (extra)
- (Preferred) You have worked with RDMBs (PostgreSQL, MySQL) or non-relational databases (Cassandra, MongoDB).
- (Preferred) You have some experience with Go, or alternatively with Object-Oriented Programming (OOP) methodologies.
- (Bonus) You have experience with Time Series data.
- (Bonus) You have experience with cloud based environments such as Amazon Web Services, Azure or GCP.
- (Bonus) Your knowledge of networking goes beyond the basics, understanding routing, proxies, VPNs, NAT, service meshes and other more complex networking concepts.
- (Bonus) You have experience using Terraform.
- (Bonus) You have experience with configuration management tools like Ansible, Chef, Puppet, Saltstack, or similar.
- 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 able to communicate effectively with your peers.