This role builds scalable AI/ML infrastructure, data pipelines and agentic applications that enable scientists in pharmaceutical research and development.

Vos tâches

Translate scientific and business needs into technical design and implementation of agentic AI solutions
Write, test and ship maintainable production code and build scalable systems and data pipelines
Apply software engineering best practices such as testing, CI/CD and documentation
Evaluate and scale ML systems using quantitative metrics and AI tooling
Contribute to architectural decisions, code reviews and evolution of development processes
Work across the stack beyond core area of expertise when needed

Ce que vous apportez

Master's degree with 2+ years of professional experience or a PhD in Computer Science or similar technical field
Experience across the ML lifecycle: GPU optimization, model performance, backend systems, cloud-native architecture
Solid knowledge of statistics, ML theory and AI/ML frameworks, libraries and toolsets
Experience with software engineering best practices: testing, clean code, documentation
Strong communication skills across technical and non-technical audiences
Willingness to work onsite approximately 3 days a week

Conditions

Taux d'activité: 100 %
Modèle de travail: Hybride
Option d'engagement fixe après la mission, si les deux parties le souhaitent

Ce qui vous attend

Onsite work approximately 3 days a week
3–6 months interim, then a permanent position

Technologies

Kubernetes
AWS

Comment postuler

Vous postulez avec votre profil Try&Hire : téléchargez votre CV, vérifiez les informations, indiquez les données clés et votre disponibilité. Une courte vidéo de présentation est facultative, mais elle aide. Notre équipe vous contacte si votre profil correspond à la mission.

Machine Learning Engineer, AI Enablement