AI & ML Engineering Specialist

Responsibilities

• Act as a technical specialist in designing, developing, and operating end-to-end machine learning and AI systems
• Work with researchers to train and optimise large scale ML models, pipelines, and agentic workflows
• Ensure the full ML lifecycle, from exploratory prototyping and experimentation to production deployment, monitoring, and continuous optimisation is implemented
• Design, build & optimise autonomous and agent based systems in a biological research context where appropriate
• Work closely with stakeholders across biology, AI research, and adjacent areas, to clarify requirements and translate complex needs into scalable ML and agent enabled solutions
• Ensure technical, regulatory, and ethical excellence in all ML and agentic systems, embedding data protection, model governance, and responsible AI principles by design

Requirements

• Bachelor’s or Master’s degree in Computer Science, Bioinformatics, Data Science, or a related field
• Significant hands-on experience in AI or Machine Learning Engineering, delivering production-grade ML solutions in complex environments
• Strong proficiency in software engineering with Python and experience with high-performance computing and/or cloud platforms (AWS and/or Azure)
• Hands-on experience with modern ML frameworks, such as PyTorch, Hugging Face, and SciKit-Learn, for training, evaluating and deploying large scale models
• Proven experience designing and operating end-to-end ML pipelines, including ingestion, training, evaluation, deployment, monitoring
• Experience with ML workflow orchestration and productionisation, e.g. using Nextflow or comparable orchestration frameworks
• Familiarity with foundation models and/or self-supervised learning in scientific or life science domains
• Practical experience with MLOps and CI/CD practices, including model versioning, automated validation, and lifecycle management
• Demonstrated ability to collaborate with cross-functional stakeholders, translating complex technical work into practical outcomes

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