Principal AI Scientist and Lead

About the role

This position is one of a kind and is the first hire into Instem’s AI & Data Sciences department. You will be building production AI on preclinical data: complex agentic systems and predictive models, including models that predict and design in vitro and in vivo studies, carried from prototype through evaluated, observable, hardened production. You will set the technical standard for how the Preclinical group builds, evaluates, and secures AI, and feed that standard into Instem's enterprise AI governance.

Responsibilities

• Build and Deploy Agentic AI Solutions
• Design and deliver production-ready agentic AI systems that automate complex preclinical workflows using advanced reasoning, orchestration, RAG, and enterprise integrations.
• Develop agent capabilities, tools, APIs, and platform services that support scalable and secure AI adoption.
• Develop Predictive & Generative Models
• Build AI models to support study design, prediction, and decision-making across in vitro, in vivo, pathology, and preclinical datasets.
• Apply advanced modelling techniques across toxicity, QSAR, PK/PBPK, omics, and endpoint prediction, ensuring robust scientific validation.
• Build the AI Data Estate
• Expand and manage the data assets that underpin Instem's AI capabilities, leveraging owned, customer-governed, public, and partner-sourced data.
• Lead AI Evaluation & Observability
• Establish evaluation frameworks, monitoring, and performance controls to ensure AI systems are accurate, reliable, explainable, and production ready.
• Partner with Scientific Stakeholders
• Collaborate with Instem scientists, pharmaceutical companies, and CROs to validate outputs, solve scientific challenges, and continuously improve AI solutions.
• Ensure Security, Governance & Compliance
• Implement secure, governed, and auditable AI practices, including model lifecycle management, access controls, and compliance with regulatory and GxP requirements.

Requirements

• PhD in Machine Learning, Computational Chemistry/Biology, Biomedical Engineering or a related field, or equivalent experience delivering production AI/ML solutions.
• Several years building and deploying AI/ML systems, ideally within preclinical research or drug discovery.
• Agentic Engineering
• Proven experience designing and deploying complex agentic AI systems in production environments.
• Strong expertise in LLMs, agent frameworks, RAG architectures, vector databases, context engineering, and enterprise integrations.
• Experienced in building evaluation frameworks, observability, security, governance, and lifecycle management into AI solutions from the outset.
• Preclinical Predictive Modelling
• Develops predictive and generative AI models using Python and modern ML frameworks.
• Experienced in applying AI to preclinical and drug discovery challenges, including toxicity prediction, QSAR, PK/PBPK, omics, and endpoint modelling.
• Strong understanding of model validation, uncertainty quantification, regulatory expectations, and scientific applicability.
• Scientific & Stakeholder Credibility
• Able to work effectively with scientists, pharmaceutical organisations, and CROs to validate models, interpret results, and communicate scientific rationale.
• Understands both the opportunities and limitations of AI models within defined contexts of use.

Skills

• Expert in Python with working knowledge of TypeScript/JavaScript and SQL.
• Exposure to Go, Rust, or other systems languages would be advantageous.

Benefits

• Comprehensive Healthcare (Medical, dental, vision, life, and more)
• Comprehensive wellbeing and support initiatives
• Clear career pathways to support you with getting to the next level
• Pro-rated and immediate vacation days
• Continuous training and development
• Generous retirement plans