MLOps Engineer @ OTA Insight in Ghent, Belgium

What you will do:

We are looking for an experienced MLOps Engineer who is passionate about designing, building and maintaining the infrastructure that supports our machine learning and statistical solutions, and wants to see their work translated into real life applications that impact 100.000’s of hotels worldwide. You will work closely with our Data R&D team to deploy, monitor and scale our models in production.

Where you will have impact:

• Design and implement the infrastructure for deploying and managing machine learning models in production.
• Together with our Data Scientists develop and maintain data pipelines using Airflow to ensure the timely delivery of high-quality data to our models.
• Deploy machine learning models to Google Cloud Platform (GCP) using VertexAI and GKE.
• Monitor the performance of our models in production, and take action to optimise their performance.
• Collaborate with our Data Scientists to improve the accuracy and reliability & scalability of our models.
• Stay up-to-date with the latest developments in MLOps technologies and best practices, and share your knowledge with the team.
• Have a strategic role in the delivery of Data R&D projects from research phase to product implementation.

About our team:

The Lighthouse Data R&D team is a team within our wider engineering team. Its mission is to maximise the power of data to create data driven culture in the industry and inside Lighthouse by providing support to existing solutions and drive innovation to reach our company and product goals.

The team works in close collaboration with our Product team, as well as a highly talented group of software engineers, devops engineers, and project managers to drive initiatives forward. We have offices in Ghent and Brussels, and as an engineer, you’ll find most of your peers there (unless they’re working from home or remote).

Today we process billions of data points and +100TB of data on a daily basis, containing hotels’ pricing information, search data, hotel bookings, etc. All of that using modern technologies. Being a growth company enables us to regularly attract new and interesting datasets, which can unlock new product directions.

What’s in it for you:

• A flexible working environment where you can work from home or, if you live nearby, at one of our seven offices around the world
• Unlimited time off: we believe in providing our employees with the flexibility and autonomy to manage their work-life balance effectively
• A motivation to deliver your best work as we have built a high-bar and very talented team of individuals that are friendly, creative, open-minded, and passionate about what they do
• Workshops and frameworks that help employees realise their full career potential
• A mandate to operationalize and democratise research through tools, training, and processes
• The opportunity to shape the products that more than 85,000 users rely on worldwide
• A choose-your-own mobility budget when you’re based in Belgium or a company car
• Extensive health insurance packages for you and your dependents prioritising our employees’ holistic well-being and healthcare needs
• Private pension funding through group insurance
• A compensation that values your work and which we will proactively keep competitive
• A referral bonus scheme when you bring new talent to our #bestteamever!

Who you are:

• +3 years of experience in MLOps or related field;
• High-energy professional with a passion for data, attention to detail, and a positive attitude;
• Strong communicator that can describe complex topics in a simple way to a variety of technical stakeholders;
• Strong experience with GCP (BQ, VertexAI, GKE);
• Experience with Python and SQL;
• Strong experience with airflow is a must;
• Experience with ML frameworks (TensorFlow, PyTorch, sklearn);
• Knowledge of CI/CD pipelines (gitlab CI in our case) and model monitoring;
• Fluent in English;
• EU Work Permit.

We welcome:

• Experience with Elasticsearch or Kibana;
• Experience with observability tools like Grafana;
• Experience with MLOps tools, like MLFlow or Kubeflow;
• Proficiency in scripting, automation, and DevOps practices.