Contract

22 days ago

Logo of FindHotel

Senior Machine Learning Platform Engineer at FindHotel

FindHotel

Apply now

Title: Senior Machine Learning Platform Engineer

Location: Amsterdam/Remote

At FindHotel, we discovered early that travel is the one thing that opens people’s minds to new ideas, cultures, and ways of thinking. Our team comes from a variety of countries and backgrounds, and share the same passion for traveling and discovering new worlds and unconventional ways of doing things. We are independent thinkers, always looking to challenge each other and get better at what we do.

Our mission is to get every traveller in the world the best accommodation deal. From adventure and backpacking to honeymoons and family vacations, we give travellers access to all the information and the available offers for their accommodation of choice. We are a passionate and diverse team of amazing humans who value and respect each other. We are spread between our HQ in Amsterdam and the countries our remote folks work from. We are growing fast and event in times like these we are being very successful.

We are looking for a Senior Machine Learning Platform Engineer to join our Data Squad in our office in Amsterdam or remotely (between UTC-3 and UTC+3 time zone) and grow with FindHotel.

At FindHotel, we make heavy use of machine learning models to make critical business decisions like pricing available hotels, projecting cancellations and bidding in marketing channels, among others. We have a diverse team of data scientists, data analysts and business users contributing to making FindHotel machine learning driven organisation. You will be part of the team evolving our Machine Learning platform to make it more scalable.

What you will actually be doing / responsibilities
  • Collaborate with other Machine Learning and Data engineers to build our next generation Machine Learning platform following current industry standards.
  • Develop batch and online inference systems at scale.
  • Create products that will enhance model monitoring and experiment tracking in production.
  • Build, deploy and manage production ready Machine Learning pipelines in collaboration with Data Scientists.
  • Deploy and manage the resources of our Machine Learning infrastructure using IaC and CI/CD best practices.
  • Collaborate with Data Scientists. Data Engineers, Data Analysts and other stakeholders to understand and fulfil their machine learning needs.
  • Work in a multi-functional agile team to continuously experiment, iterate and deliver on new product objectives.
  • Iterate continuously using best practices to upgrade our effort in achieving world class Machine learning platform
What can you expect at the beginning of this experience?
  • In your first week, you will get acquainted to the squads, its codebase and the tooling, with the goal of shipping something to production and build confidence early on.
  • In your first month, you will get to know more people from the other squads and disciplines, in order to understand the foundation of the business and the various bits it is made of.
  • One quarter in, you will be effectively an active member of your squad and your teammates will fully count on you; you will have built meaningful relationships within the company and be comfortable discussing ideas, inside and outside of your squad’s scope; ideally, you will have presented a topic you are fond of in one of our internal knowledge sharing sessions and/or demoed some work the team did during our weekly all-hands meeting.
Typical day activities
  • Attend the daily standup with your squad where you will track how the current sprint is going towards the sprint goal, identify any possible blocker and adapt accordingly.
  • Meet your peers to discuss the design of the next machine learning platform product.
  • Build a new module of the machine learning platform to help data scientist and business people improve their work.
  • Test a new tool or framework that could be used in our machine learning environment.
  • Participate in peer programming and mentoring sessions to improve your coding skills and engineering practices.
Who we are looking for
  • You are willing to build a career in Machine Learning engineering and grow into a reference at FindHotel.
  • You have strong experience with cloud platforms and you like to get your hands dirty with them.
  • You understand the needs of Data Scientists and you love to create tools to improve their work.
  • You know your way with Python and you also manage with other languages like Go.
  • You are knowledgeable about what it takes to build a scalable Machine Learning platform and you are willing to put the components together.
  • You can manage end to end deployment of Machine Learning models and include the various necessary touch points.
  • You are not scared of data science algorithms and don’t view them as just another blackbox
  • You are pragmatic and curious, and you love to get things done.
  • You engage with your team and all the engineering group actively, sharing knowledge and best practices in order to improve with them every day.
  • You are familiar with Agile Methodologies.
Bonus points for:
  • Experience with AWS, Terraform and GitHub Actions.
  • Experience with modern MLOPs concept.
  • Experience with Snowflake.
What we offer
  • Challenging problems and tech to work on.
  • Growth opportunities within the team and cross-functionally.
  • An amazing team of curious and diverse personalities, with a passion for learning (everyone has access to an annual learning budget to attend conferences or courses).
  • A growing remote culture where you have a chance to deeply influence the way we work with each other.
  • A competitive compensation package and Stock Appreciation Rights.
  • Flexible time off (take as many holidays as you need) and a chance to work remotely – we measure results, not time spent at keyboard.
  • Annual company retreat in some great location – check out our Antalya trip in 2022.
  • For a remote role, regular trips to Amsterdam’s HQ (depending on team priorities, 1-4 times a year).

From remote.co