Teams at Relation Therapeutics

Design and implement generative and predictive models of cellular behavior using biological and single-cell perturbation data. Develop models for generalization, counterfactual prediction, causal reasoning, and experimental design. Collaborate with experimental biology teams to validate computational hypotheses, evaluate mechanistic fidelity, and guide real-world interventions. Communicate findings across interdisciplinary teams while contributing to a matrixed, collaborative research environment.

Lead Relation’s Platform Engineering team and technical strategy for hybrid on-premises and cloud infrastructure supporting machine learning, scientific computing, genomic pipelines, and internal services. Own Kubernetes architecture, MLOps environments, CI/CD, developer tooling, observability, disaster recovery, platform security, and governance. Hire and develop engineers, guide technical direction, manage production operations and incidents, and partner with Engineering, Data Science, and Machine Learning stakeholders.

Design, implement and optimise large neural network models and scalable training pipelines. Build distributed multi-GPU/multi-node training, profile and optimise GPU workloads, maintain core ML infrastructure, and productionise research models for downstream biological discovery workflows.