Machine Learning Engineer
Hostelworld
Porto, Porto District, PT
há 1 dia
source : BidRecruit Ltd.

ABOUT US

We are Hostelworld Group, the largest global hostel-focussed booking platform. With more than 13 million reviews across 17,800 hostels in 179 countries, Hostelworld is an online hub for social travel.

The website is available in 19 languages and our mobile app in 13 languages.

Our customers crave cultural connection and unique experiences, and Hostelworld makes this possible. We inspire them to meet the world and come back with stories about life-changing experiences, by providing an unbeatable selection of hostels wherever they want to travel.

Hostelworld has a growing team of over 200 people within Technology, Product, Global Markets, HR, Finance & Legal and Marketing, across our Dublin, London, Porto, Shanghai, and Sydney offices.

Founded in 1999 and headquartered in Dublin, Hostelworld is listed on the London Stock Exchange and Dublin Euronext.

Working at Hostelworld means embracing a start-up ethos, combined with a professional and mature approach to growing and scaling as a publicly listed business.

We value collaboration, innovation, respect, communication, and smart thinking.

THE ROLE & TEAM

Hostelworld is structured differently than most tech companies in 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 progress on building products that help travellers find the right inventory of hostels and experiences.

We’re looking for an individual that has experience understanding the dynamics of a 2-sided marketplace. You will help identify opportunities to optimize the marketing budget and bids across different channels using data science to automatically and efficiently acquire customers, driving massive business growth.

ROLE RESPONSIBILITIES

  • Translate business and customers problems into machine learning solutions.
  • 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 serving production models at scale.
  • Define hypotheses, measure and monitor the success of the machine learning solutions.
  • 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.
  • SKILLS AND EXPERIENCE

    Experience & Qualifications :

  • Proficiency in machine learning concepts such as data exploration, feature engineering, model selection, training and testing.
  • Proven experience in productization of machine learning solutions libraries, packages, REST APIs, serving and monitoring.
  • You have direct experience building successful data science products for performance marketing.
  • Familiarity with natural language understanding or image processing.
  • Familiarity with deep learning.
  • Knowledge & Skills :

  • Proficiency programming in Python and SQL-like databases.
  • You are proficient in at least one of the following machine learning tasks classification, regression or clustering.
  • You are proficient with at least two of the following libraries or packages scikit-learn, pandas, Spark MLlib, TensorFlow or PyTorch.
  • Ability to carefully design solutions that scale with increasing volumes of data.
  • Ability to follow software engineering best practices, including requirements analysis, system design, modularity, version control, testing and documentation.
  • Please note this role is available in Shanghai & Porto - please specify your preference.

    We welcome applications from all backgrounds and commit to ensuring equal opportunities for everyone

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