Quotient Sciences is a leading drug development and manufacturing accelerator that helps biotech and pharma companies bring new medicines to patients faster. As an AI Engineer, you will own the full AI lifecycle and build technical foundations that enable delivery of AI products aligned with our strategic objectives.
Requirements
- Design, develop, and deploy AI and machine learning models to solve business problems and deliver measurable value.
- Test and select modelling approaches balancing performance, interpretability, and operational fit.
- Build and maintain scalable ML pipelines and infrastructure for classical ML and deep learning.
- Deploy models to production using containerisation, CI/CD, and MLOps toolsets; manage ongoing configuration and administration.
- Develop LLM-based tools using prompt engineering, retrieval, and embedding pipelines for knowledge retrieval and workflow assistance.
- Build APIs, microservices, or workflow components to integrate AI tools into existing systems.
- Set up monitoring for model drift, performance, latency, and failures; maintain logging and observability standards.
- Embed responsible AI practices, governance, and compliance in all solutions; follow GxP and validation standards where required.
- Collaborate with cross-functional teams to translate business requirements into technical solutions.
- Produce clear documentation for models, pipelines, deployment steps, and operational expectations.
- Communicate complex technical concepts in clear, actionable terms to technical and non-technical stakeholders.
- Mentor and coach team members; foster a collaborative, high-performance culture.
- Stay current with advancements in AI/ML and data engineering; help shape common frameworks and best practices across the organisation.