Join our AI Engineering team

We're not a strategy firm that ships slide decks and walks away. Not a tech consultancy that builds what won't get adopted. Not a product company chasing problems it doesn't understand. We're all three at once: strategy, deep technical and integration expertise, and product, working as one. That combination is our flywheel. Consulting keeps us close to the hardest real-world problems. Products let us solve them at scale. Every engagement sharpens our products; every deployment makes the next engagement faster, deeper, and more certain.

We're obsessed with outcomes. While 95% of enterprise AI pilots never reach production, Visium is built to be the 5% delivering productised AI that compounds in value, not point solutions that deliver marginal gains. We are AI-native, not AI-adjacent. We don't bolt AI onto broken workflows; we redesign them with AI at the core.

Our AI Engineering team builds, deploys, and scales real-world AI systems that create measurable business impact. By joining our team, you'll be working end-to-end. You’ll typically be involved in:

• Translating business problems into AI-driven solutions
• Industrializing ML models (from prototype to production)
• Designing and maintaining AI pipelines and platforms
• Ensuring performance, monitoring, and continuous improvement of AI systems
• Shaping best practices around MLOps, architecture, and AI governance

Join us!

We’re always excited to connect with great talent. By joining this talent pool, you’ll be matched with relevant opportunities as they open within our AI Engineering team. Here you have some details on what we look for:

• Experience in AI / Machine Learning Engineering roles
• Solid software engineering skills (Python required; others are a plus)
• Hands-on experience deploying ML models into production environments
• Strong understanding of MLOps (CI/CD for ML, monitoring, versioning, retraining)
• Experience with cloud platforms (Azure strongly preferred)
• Knowledge of containers and orchestration (Docker, Kubernetes)
• Ability to design scalable, secure, and maintainable AI systems

• Experience with LLMs, GenAI, or advanced ML use cases
• Previous exposure to healthcare projects in the intersection with AI.
• Strong communication skills and a consulting mindset
• Fluency in French/German