Job details
● 💼 Engineering Team
● 📍 Belgium - Ghent
● 🕜 Full-Time/Hybrid

What you will do

Reporting to our Director of Data Science, you will be a key player in our Data Organisation. As our new Senior MLOps Engineer, your mission is to design, build, and maintain the robust infrastructure that powers our machine learning solutions, from classical models to new LLM-powered features and AI agents. Your role has a crucial enablement mandate: you will not only serve the Data R&D team but also set up the foundations that empower other engineering teams to ship their own AI features into production, directly impacting hundreds of thousands of hotels globally.

Where you will have impact

• Design and implement the core infrastructure for deploying and managing both classical machine learning models and generative AI systems in production.
• Develop and maintain robust data pipelines using Airflow to ensure the timely delivery of high-quality data to our models.
• Deploy, monitor, and optimize the performance of machine learning models on Google Cloud Platform (GCP) using tools like VertexAI.
• Act as a force multiplier by creating foundational tools and providing guidance that enables other engineering teams to ship their own AI features.
• Collaborate closely with our Data Scientists to continuously improve the accuracy, reliability, and scalability of our models.
• Play a strategic role in the end-to-end delivery of Data R&D projects, from the research phase through to product implementation.
• Stay at the forefront of MLOps technologies and best practices, sharing your knowledge to elevate the entire team.

About our team

You'll be joining the Data R&D team, a core group on a mission to maximize the power of data. We support existing solutions and drive innovation, processing billions of data points daily to unlock new value for the hospitality industry. In this role, you will work closely with a wide range of technical collaborators, including your Senior MLOps peer, our Data Science teams, the DevOps team on GCP infrastructure, the Data Platform team on data quality and pipelines, and Product Backend Engineers to guide them in building their own AI-powered features.

What's in it for you?

• Flexible time off: Autonomy to manage your work-life balance.
• Career development: Workshops, frameworks, and trainings to maximize your professional potential.
• Impactful work: Shape products relied on by 85,000+ users worldwide.
• Mobility options: Mobility budget or company car (based on your job category).
• Net allowance: Support for home office related expenses.
• Vouchers: Lunch vouchers & Eco vouchers.
• Comprehensive health insurance: Extensive coverage for you and your dependents.
• Pension funding: Group insurance to secure your future.
• Referral bonuses: Earn rewards for bringing in new talent.

Who you are

• You have significant experience in an MLOps role, with a proven track record of putting machine learning models, including Generative AI, into production at scale.
• You have strong, hands-on experience with Google Cloud Platform (GCP), particularly with services like BigQuery, and VertexAI.
• You are highly proficient with Python and SQL.
• You have strong experience building and maintaining data pipelines with Airflow.
• You are familiar with common ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• You understand CI/CD pipelines (we use GitLab CI) and model monitoring principles.
• You are a strong communicator who can explain complex technical topics to a variety of stakeholders.
• You are curious, open-minded, and proactive, with a passion for exploring AI's capabilities in your own development work.

We welcome

• Experience with MLOps tools like MLflow or LLM-specific infrastructure like an Agent Development Kit (ADK).
• Familiarity with observability tools such as Grafana.
• A solid understanding of DevOps practices, including scripting and automation.

Technologies you will work with

Python, SQL, BigQuery, VertexAI, GKE, Cloud Run, Docker, Kubernetes, Terraform, Apache Airflow, GitLab CI/CD, Dataflow, scikit-learn, MLflow, VertexAI, ADK, Grafana.

Job details
● 💼 Engineering Team
● 📍 Spain - Barcelona
● 🕜 Full-Time/Hybrid

What you will do

Reporting to our Director of Data Science, you will be a key player in our Data Organisation. As our new Senior MLOps Engineer, your mission is to design, build, and maintain the robust infrastructure that powers our machine learning solutions, from classical models to new LLM-powered features and AI agents. Your role has a crucial enablement mandate: you will not only serve the Data R&D team but also set up the foundations that empower other engineering teams to ship their own AI features into production, directly impacting hundreds of thousands of hotels globally.

Where you will have impact

• Design and implement the core infrastructure for deploying and managing both classical machine learning models and generative AI systems in production.
• Develop and maintain robust data pipelines using Airflow to ensure the timely delivery of high-quality data to our models.
• Deploy, monitor, and optimize the performance of machine learning models on Google Cloud Platform (GCP) using tools like VertexAI.
• Act as a force multiplier by creating foundational tools and providing guidance that enables other engineering teams to ship their own AI features.
• Collaborate closely with our Data Scientists to continuously improve the accuracy, reliability, and scalability of our models.
• Play a strategic role in the end-to-end delivery of Data R&D projects, from the research phase through to product implementation.
• Stay at the forefront of MLOps technologies and best practices, sharing your knowledge to elevate the entire team.

About our team

You'll be joining the Data R&D team, a core group on a mission to maximize the power of data. We support existing solutions and drive innovation, processing billions of data points daily to unlock new value for the hospitality industry. In this role, you will work closely with a wide range of technical collaborators, including your Senior MLOps peer, our Data Science teams, the DevOps team on GCP infrastructure, the Data Platform team on data quality and pipelines, and Product Backend Engineers to guide them in building their own AI-powered features.

What's in it for you?

• Flexible time off: Autonomy to manage your work-life balance.
• Alan Flex benefits: 160€/month for food or nursery.
• Flexible retribution: Optional benefits through tax-free payroll deductions for food, transportation and/or nursery. 
• Wellbeing support: Subsidized ClassPass subscription.
• Comprehensive health insurance: 100% Alan coverage for you, your spouse, and dependents.
• Impactful work: Shape products relied on by 85,000+ users worldwide.
• Referral bonuses: Earn rewards for bringing in new talent.

Who you are

• You have significant experience in an MLOps role, with a proven track record of putting machine learning models, including Generative AI, into production at scale.
• You have strong, hands-on experience with Google Cloud Platform (GCP), particularly with services like BigQuery, and VertexAI.
• You are highly proficient with Python and SQL.
• You have strong experience building and maintaining data pipelines with Airflow.
• You are familiar with common ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• You understand CI/CD pipelines (we use GitLab CI) and model monitoring principles.
• You are a strong communicator who can explain complex technical topics to a variety of stakeholders.
• You are curious, open-minded, and proactive, with a passion for exploring AI's capabilities in your own development work.

We welcome

• Experience with MLOps tools like MLflow or LLM-specific infrastructure like an Agent Development Kit (ADK).
• Familiarity with observability tools such as Grafana.
• A solid understanding of DevOps practices, including scripting and automation.

Technologies you will work with

Python, SQL, BigQuery, VertexAI, GKE, Cloud Run, Docker, Kubernetes, Terraform, Apache Airflow, GitLab CI/CD, Dataflow, scikit-learn, MLflow, VertexAI, ADK, Grafana.

We’re looking for a Medior or Senior Data Scientist with at least 3 years of experience and a proven track record in developing Generative AI applications. In this role, you’ll apply your expertise in Machine Learning and AI technologies to solve complex challenges and deliver impactful, data-driven solutions.

Your Role

• Design and develop AI applications (e.g., virtual assistants) that improve user experiences, empower employees with intelligent tools, and automate internal processes.
• Apply a wide range of analytical techniques, including Generative and Predictive AI methods such as:
  • Prompt Engineering, RAG, Fine-Tuning, Speech-to-Text, NLP, Image Generation, and Agentic AI.
  • Classical Machine Learning and Statistical Modeling approaches.
• Build and deploy AI models into production, leveraging your strong programming skills in Python and familiarity with modern AI frameworks.
• Present insights and results clearly to stakeholders and decision-makers.
• Work with diverse and large-scale datasets, applying your analytical mindset to extract meaningful insights.
• Collaborate in a lean, innovative, and Agile environment where open communication, teamwork, and shared learning are valued.

Your Profile

• Education: Master’s degree (or equivalent experience) in a quantitative field such as Statistics, Mathematics, Computer Science, or Engineering. Candidates with other backgrounds but strong analytical expertise are welcome.
• Experience: Minimum 3 years in Data Science and Analytics, with hands-on experience in Deep Learning and pre-trained models.
• Technical Skills (Required):
  • Python, Deep Learning frameworks (e.g., PyTorch, TensorFlow)
  • Experience with pre-trained and Generative AI models
• Technical Skills (Preferred): Tools like Domino, Git, and frameworks for GenAI (e.g., Prompt Engineering, Fine-Tuning, LangGraph, ADK, MCP)
• Business Experience (Preferred): Experience developing GenAI applications in Finance or similar domains
• Soft Skills:
  • Team player with a business-oriented mindset
  • Proactive, autonomous, and committed to results
  • Strong communication and influencing abilities
  • Excellent analytical and problem-solving skills
  • Comfortable working in a dynamic, multicultural environment