Description
This role builds scalable AI/ML infrastructure, data pipelines and agentic applications that enable scientists in pharmaceutical research and development.
Tasks
- 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
Profile
- 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
Offer
- Onsite work approximately 3 days a week
- 3–6 months interim, then a permanent position
Company
Pharmaceutical research