Senior Machine Learning Engineer

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Are you a passionate Senior Machine Learning Engineer eager to take on a new challenge that has the potential to revolutionize the European Job Ads Market? Then keep reading!

We're seeking a Senior Machine Learning Engineer to join our cross-departmental Data Science unit. In this high-impact role, you'll work across multiple teams and projects throughout the organization, leading the development and deployment of production ML systems that serve diverse business needs. As a senior member of our team, you'll be responsible for architecting scalable ML infrastructure, mentoring team members, and driving technical excellence as we transform data science prototypes into robust production services that deliver value across the enterprise.

• Partnering with Data Science to translate experimental models into scalable, production-grade ML systems
• Designing and build high-performance, low-latency model-serving architectures and infrastructure
• Defining and enforce best practices for ML productionization, including coding standards, testing, and deployment strategies
• Leading cross-functional collaboration between Data Science, Engineering, and Operations as the primary technical interface
• Defining and implementing model performance monitoring (e.g., drift detection, data quality, inference metrics) to ensure reliability in production
• Driving innovation by evaluating new tools, frameworks, and methodologies, and promoting their adoption across the organization
• Developing and maintain technical documentation, system designs, and operational runbooks.

• 5+ years of experience in ML Engineering, MLOps, or closely related roles
• Proven experience deploying and maintaining machine learning models in production at scale
• Strong Python skills, including experience with data and ML ecosystems
• Familiarity with LLMs, RAG, and emerging AI paradigms (e.g., agent-based systems)
• Hands-on experience with cloud platforms (e.g., AWS) for building and operating ML systems
• Experience with containerization (Docker) and building production-ready services
• Demonstrated ability to lead technical projects and make architectural decisions
• Full professional proficiency in English

• 10 days fully paid sick leave per year
• 25 days of annual vacation leave
• Full private health coverage (employee + up to 2 children to age 20)
• Gym allowance
• Workation
• Hybrid & flexible working (team-based arrangement)

• Presentation of the project and company (30 mins)
• Conversation with hiring manager (1 hour)
• Technical challenge (at your best convenience)
• Challenge presentation (1h-1.5 hour)Offer