Senior ML Engineer | Software engineer

Xccelerated | Part of Xebia; Amsterdam; Hybrid; EUR 70,000 - 110,000; Full time

Benefits offered by this job

Technical trainings & Innovation days

Challenging assignment

Macbook and Iphone

Lunches, coffee & snack bar

Flexible work from home & office in AM

Job summary

Xccelerated | Part of Xebia is seeking a Senior Data Scientist to join our Data team at the intersection of Data Science and ML Engineering in Amsterdam. You will help turn data into tools and models that support flight operations and decisions in a live environment.

You’ll work on productionizing AI/ML models for delays, maintenance, and crew scheduling, with a focus on robust, scalable solutions. You’ll collaborate across teams, work with Spark, Kafka, Airflow, Kubernetes, and GenAI frameworks

Qualifications

• 4-6 years of experience as a Data Scientist or ML(OPS)
• Hands-on experience with modeling and getting models into production
• Experience with open-source tools such as Spark, Kafka, Airflow or Kubernetes
• Demonstrated experience with GenAI implementations (RAG pipelines)

Responsibilities

• Extract insights from operational and flight data sources
• Build and productionize AI/ML models for flight delays, maintenance planning, and crew scheduling
• Contribute to large-scale optimization and simulation projects
• Develop tools to make complex processes transparent for planners and crews
• Work with real-time data and smart calculations to improve passenger and crew experience

Skills

Customer focus

Can-do attitude

Results oriented

Willingness to learn

Education

Data Science / Analytics / AI background

Tools

Spark

Kafka

Airflow

Kubernetes

Job description

We're looking for a Senior Data Scientist to join our growing Data team working at the intersection of Data Science and Machine Learning Engineering. As part of this team, you'll turn that data into tools and models that help crews and planners make better, faster decisions and build sustainable solutions for the aviation of the future.

This isn't a role about isolated proof-of-concepts. The focus is on getting models robust and running at scale in a live environment: from analysis and model development through to testing, monitoring and maintaining them once they're actually in use.

What you'll work on

• Extracting insights from fast-growing operational and flight data sources
• Building and productionizing AI/ML models that predict flight delays, optimize maintenance planning, and support smarter crew scheduling.
• Contributing to large-scale optimization and simulation projects
• Developing tools that make complex operational processes more transparent for planners and crews, supporting faster decision-making
• Working with real-time data and smart calculations to improve the passenger and crew experience

This is you

From a personal perspective, you are customer focused and have a strong can-do mentality. You focus on results, have a desire to complete challenging tasks and learn while doing. Next to this, you have:

• A background in Data Science, Business Analytics, or Artificial intelligence
• 4-6 years of work experience as a Data scientist or ML(OPS)
• Hands-on experience with both the Data Science side (modeling, analysis) and the Machine Learning side, including getting models into production
• Knowledge of open-source technologies like Spark, Kafka, Airflow or Kubernetes
• Demonstrated experience with production-grade GenAI implementations (modern GenAI/LLM frameworks such as RAG pipelines)

What Xccelerated offers

• Technical trainings & Innovation days for a full year (every week)
• Challenging assignment
• Macbook and Iphone
• Lunches, amazing coffee and snack bar
• Flexibility in working from home & at the office in Amsterdam

Interested? We'll love to meet you!

Please get in touch! Contact Samantha Alves Goncalves at [e-mail] or by phone at 0613889770.

Application Process

• First interview with one of our Recruitment consultants
• Technical interview with one of our Technical leads

We aim to complete an application process (from application to offer) within 1-3 weeks. As you will un