Do you love working with clean code and best practices? Keep reading!
If you want to be part of a fast-growing project where you can apply and develop your technical skills and you are ready to handle some of the technology's greatest challenges, then keep reading!
Our client is changing the fashion game and has become the leading fashion social network in Europe - through technology and talent. More than 6 million users come to get inspired by their favorite influencers and friends ready-to-shop content.
But hey! They are still an engineer company.
What will you do?
You will be a part of a team that handles push notification algorithms and scheduling. Furthermore, they handle the logic for the purchases (purchases detection, fraud validation). As a part of this team you will ensure robustness, performance and failure characteristics of the system.
You will also work closely with the product team in creating roadmaps and timelines for product development.
You will enjoy...
- Flexible schedule
- Possibility to move festive days
- Great life-work balance
- Fruits and coffee at the office
- Afterwork once per month
- Weekly trainings
Super if you have...
- BS degree in Computer Science, similar technical field of study or equivalent practical experience.
- Strong OOP and software design skills.
- Proven track record building robust search systems with Lucene / Elasticsearch / Solr or other noSQL.
- Extensive experience in Java or other OO languages, ideally using TDD, DDD, Clean and/or other best practices.
- Experience running applications on AWS, with the support from the DevOps team.
- Passionate about developing high-quality enterprise software.
- Experience building highly scalable applications with a large amount of traffic.
- Happy to take an active role in supporting the business needs.
BOOM! if you have...
- Expertise in personalization and recommender systems.
- Solid understanding of search metrics and implementing tracking to measure performance.
- Solid understanding of search engines and utilizing features effectively.
- Experience building search capabilities using natural language processing technique.
- Hands-on experience developing and implementing Machine Learning algorithms and models. Background in Machine Learning & Information Retrieval.