An ambitious, deep-tech organisation at the forefront of biotechnology and artificial intelligence is seeking a visionary Head of AI to lead the development of next-generation biological foundation models.
Underpinned by the world’s most comprehensive and ethically sourced database of natural biodiversity, our platform enables cutting-edge research and discovery across academia and industry. Following a successful Series B funding round (£47 million), we are expanding our AI capabilities to develop state-of-the-art models and algorithms that will shape the future of biology and bioengineering.
This is a unique opportunity to lead a high-performing AI team, influence partnerships with global technology leaders, and build on an exceptional data infrastructure that is entirely new to science.
Key responsibilities
- Lead and manage a team of AI and machine learning researchers/engineers, providing technical direction and fostering a culture of creativity and rigour
- Design and implement novel AI/ML models and algorithms, balancing exploratory research with robust, scalable solutions
- Collaborate closely with interdisciplinary teams of biologists, bioinformaticians, and engineers to translate research objectives into applied outcomes
- Oversee multiple concurrent research streams, ensuring strategic alignment with organisational goals
- Contribute to the overall AI systems architecture, supporting the transition from research prototypes to production-level tools
- Represent the company’s AI leadership through academic and industry collaborations, conferences, and publications
- Provide mentorship and guidance to junior and senior members of the AI team
- Shape and execute a long-term AI strategy rooted in novel biological data and real-world application
Essential
- A postgraduate degree (PhD or MSc) in Computer Science, Machine Learning, Computational Biology or a related field
- At least 5 years of industry experience in AI/ML research or engineering, with a minimum of 4 years in a technical leadership role or 3 years in people management
- A strong publication record or equivalent practical expertise in areas such as generative AI, deep learning, or computational biology
- Proven experience applying AI techniques to biological challenges, particularly in areas like protein design or genomics
- Demonstrated success in leading high-impact AI projects and delivering real-world solutions
- Exceptional communication skills, capable of engaging with both technical and non-technical stakeholders
- Experience training large generative models, including distributed training across GPU clusters or cloud platforms (e.g. AWS, Azure, Lambda)
- Strong critical thinking, strategic planning, and problem-solving abilities
Desirable
- Experience in protein or DNA bioinformatics
- Proficiency in MLOps and machine learning infrastructure
- Background in software engineering and data pipelines (e.g. using Airflow)
- Familiarity with cloud-based model deployment
- Exposure to Agile project management methodologies
This is a rare opportunity to shape the future of AI-driven biotechnology from both a strategic and technical perspective, working with a uniquely rich dataset and an ambitious cross-functional team.