MLOps & AI Engineering Manager

As a Product Owner, you will be part of a larger AI team (+/- 45 people) and report to the AI director. The AI team is responsible to create value with AI throughout the company:

• Create AI to make our commercial approach as personal as possible (Segment of 1)
• Maximize efficiency & effectiveness in our customer operations
• Understand product experience by our customers and build the right intelligence to find root causes and tailored customer solutions
• Roll-out, maintain and operate our networks as smart and automated as possible

“With big impact comes big responsibility!” To deliver sustainable value, our AI products must be responsible and reliable.
You will be end-to-end responsible for how AI products are built and industrialized, leading the Machine Learning Operations team while guiding and steering AI Tech Leads.

Your Key Roles & Responsibilities

• Leadership & Team Management: Build, mentor, and lead a high-performing MLOps team (4 people) and guide AI Tech Leads (6 people).
• AI Implementation Strategy: Define and steer AI implementation (build & operate AI and own the AI platform) from a functional and technical perspective.
• ML Model Selection & Strategy: Ensure the right AI/ML models are chosen for the right problems, balancing business impact and technical feasibility.
• AI Risk Management: Own and implement the AI Risk Management framework to ensure responsible AI.
• Cross-Functional Collaboration: Partner with AI Product Owners, AI Architects, AI Tech Leads & the Guild Lead to set the right priorities in a continuously evolving environment.

Qualifications & Experience

✅ Education & Experience:

• Master’s or PhD in Computer Science, AI, Machine Learning, or related field.
• 10+ years in AI/ML engineering, with 3+ years in leadership roles.
• Proven experience deploying and managing ML models in production.

✅ Technical Skills:

• Thought leader in choosing the right ML models for business problems.
• Strong expertise in MLOps, CI/CD, and model lifecycle management.
• Hands-on experience with AWS ML services (SageMaker, Lambda, EKS, Step Functions) and proficiency in Terraform, Docker, Kubernetes, and model monitoring tools.
• Knowledge of AI governance, risk management, and compliance.

✅ Leadership & Collaboration:

• Experience leading MLOps teams and coaching AI Tech Leads.
• Strong stakeholder management and cross-functional collaboration.
• Agile & DevOps mindset in a fast-changing environment.

How we make a difference for you!

• Start a new adventure in the beating heart of our data driven organization, where we work in the utmost flexible way, be it from home or from our open and trendy collaboration spots at the office.
• Collegiality is more than just a word.
• We keep an eye out for talent, ambition and eagerness to learn. 
• We’ll coach you, train you and make you part of our story.
• Moreover, you’ll enjoy a wages and benefits package that will get you places. We’re talking mobility budget, meal vouchers, group and health insurance, a yearly bonus and discounts on Telenet products. Come experience it for yourself, our passion is contagious.