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

I Suoi compiti

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

Che cosa porta con sé

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

Condizioni quadro

Grado di occupazione: 100 %
Modello di lavoro: Ibrido
Opzione di assunzione a tempo indeterminato dopo l'incarico, se entrambe le parti lo desiderano

Che cosa La aspetta

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

Tecnologie

Kubernetes
AWS

Come candidarsi

Si candida con il Suo profilo Try&Hire: carichi il CV, verifichi i dati, inserisca i dati principali e la disponibilità. Un breve video di presentazione è facoltativo, ma aiuta. Il nostro team La contatterà se il Suo profilo è adatto all'incarico.

Machine Learning Engineer, AI Enablement