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

Ihre Aufgaben

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

Was Sie mitbringen

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

Rahmenbedingungen

Pensum: 100 %
Arbeitsmodell: Hybrid
Option auf Festanstellung nach dem Einsatz, wenn beide Seiten wollen

Was Sie erwartet

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

Technologien

Kubernetes
AWS

So bewerben Sie sich

Sie bewerben sich mit Ihrem Try&Hire-Profil: Lebenslauf hochladen, Angaben prüfen, Eckdaten und Verfügbarkeit eintragen. Ein kurzes Vorstellungsvideo ist freiwillig, hilft aber. Unser Team meldet sich, wenn Ihr Profil zum Einsatz passt.

Machine Learning Engineer, AI Enablement