.ABOUT US Hostelworld Group, the global hostel-focused online booking platform, inspires adventurous minds to meet the world and come back with life-changing stories to tell.
Our customers are not your average tourists; they crave cultural connection and unique experiences that we make possible by providing an unbeatable selection of hostels in unmissable locations – all in the palm of their hand.
It is the social nature and community feel of hostels and their environment that enable travellers to embrace journeys of discovery, adventure, and meaning.
We have more than 13 million reviews across 17,800 hostels in more than 179 countries, making the brand the leading online hub for social travel.
The website operates in 19 different languages and our mobile app in 13 languages.
Founded in 1999 and headquartered in Dublin, Hostelworld has a growing, high-calibre team of 230 people within Technology, Product, Global Markets, HR, Finance & Legal, and Marketing Teams across our Dublin, London, Porto, Shanghai, and Sydney offices.
Hostelworld is listed on the London Stock Exchange and Dublin Euronext.
You can read more about our story here.
LOCATION This role is based in Portugal.
We have an office space in central Porto for those who prefer a hybrid model where you can spend time with colleagues in-person.
If necessary, the role can be remote within Portugal with coming together for team meetings as needed.
WHO YOU'LL WORK WITH Hostelworld is structured differently than most tech companies in the world, as we do not have an Engineering or Product department.
Instead, we have "Growth Teams" which are full-stack groups that are organised into cross-functional squads.
As a Machine Learning Engineer, you will play a key role in shaping the Data Science Growth Team's progress on building products that help travellers find the right inventory of hostels and experiences.
WHAT YOU'LL DO Translate business and customer problems into machine learning solutions.
Define hypotheses, measure, and monitor success.
Propose, design, build, maintain, and push machine learning solutions into production.
Express and communicate the business and technical impact of the machine learning solutions to a variety of audiences.
Responsible for the end-to-end process of designing and running experiments to serve production models at scale.
Ensure that the solutions are maintainable, performant, scalable, and debuggable.
Automate and abstract away different repeatable routines that are present in most machine learning tasks.
Provide support to software engineers and product managers building machine learning solutions.
Bring the best software development and infrastructure practices to the data science squad.
WHAT WE'RE LOOKING FOR Experience & Qualifications: Proficiency in machine learning concepts such as data exploration, feature engineering, model selection, training, and testing