Data Scientist / ML Engineer – GenAI (Engineering & Maintenance)
At Sytac, we build high-performing engineering teams for leading organizations in the Netherlands and beyond. We combine a pragmatic, people-first culture with strong technical craftsmanship giving engineers autonomy in real production environments, backed by a consultancy that invests in growth, community, and long-term partnerships.
For one of our large, complex, and operationally critical clients in the aviation domain, we are looking for a Data Scientist / ML Engineer with strong GenAI experience. You’ll join an Engineering & Maintenance data program where AI solutions directly influence day-to-day operations, cost efficiency, safety, and customer experience.
This role sits at the intersection of data science, machine learning engineering, and real-world production systems. The models you work on are used 24/7 in live operational and customer-facing contexts.
What you’ll do
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Design, develop, and deploy GenAI and LLM-based solutions used in live operational environments
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Work closely with engineers, mechanics, and business stakeholders to deeply understand real operational problems before designing solutions
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Perform exploratory data analysis to assess data quality and identify improvement opportunities
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Engineer features by combining traditional data warehouses with large-scale data lakes and new data sources
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Run experiments and track model metrics, parameters, and metadata using model registries
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Bring models to production in collaboration with data engineers and platform teams, following enterprise-grade standards
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Own models end to end: monitoring, retraining, performance improvements, and lifecycle management
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Contribute to cloud-native data science development, building and migrating solutions directly in the cloud
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Translate data science requirements into architectural decisions and ways of working
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Share learnings and best practices within engineering and data communities
You are encouraged to spend 15–20% of your time on learning and research, exploring new technologies, papers, or experimental projects that strengthen your impact as a data professional.
What we’re looking for
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Strong experience as a Data Scientist or ML Engineer working on production-grade solutions
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Hands-on experience with GenAI / Large Language Models
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Solid software engineering skills, with production-level Python
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Deep understanding of MLOps, including deployment, monitoring, logging, and retraining
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Experience working with large-scale or big data environments
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Comfortable operating in complex, real-world operational contexts
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Able to clearly explain technical solutions to non-technical stakeholders
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Proactive, analytical, and ownership-driven mindset
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Fluent professional working proficiency in English
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EU residency (no sponsorship possible)
Nice to have
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Experience with Graph Analysis, Agentic AI, or GraphRAG
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Exposure to cloud platforms (GCP is a strong plus)
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Experience with tools such as Docker, Git, SQL, and observability platforms
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Familiarity with Agile / Scrum ways of working
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Experience working with external partners or suppliers
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Background in Engineering & Maintenance, aviation, or other asset-heavy domains
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