MachineLearningEngineer (Medical & Drug Discovery) Oxford (2 days a week onsite) Competitive (Up to £85,000, DOE) Join a leading innovator in medical and drug discovery, using AI to accelerate healthcare breakthroughs. If you're passionate about applying machinelearning to complex biological challenges … this is your chance to make a real impact. Role Overview: As a MachineLearningEngineer, you'll design and optimize AI models to advance biomedical research. You'll collaborate with data scientists, bioinformaticians, and scientific experts to transform large datasets into actionable insights. Key Responsibilities: Develop … ML models for protein structure, drug-target interactions, and biomarker discovery. Build data pipelines for large biomedical datasets (genomics, clinical, molecular). Implement deep learning models (e.g., CNNs, RNNs, transformers) for biological analysis. Apply NLP to process biomedical literature and clinical data. Collaborate with cross-disciplinary teams to ensure More ❯
Job Description MachineLearningEngineer (Medical & Drug Discovery) Oxford (2 days a week onsite) Competitive (Up to £85,000, DOE) Join a leading innovator in medical and drug discovery, using AI to accelerate healthcare breakthroughs. If you're passionate about applying machinelearning to complex … biological challenges, this is your chance to make a real impact. Role Overview: As a MachineLearningEngineer, you'll design and optimize AI models to advance biomedical research. You'll collaborate with data scientists, bioinformaticians, and scientific experts to transform large datasets into actionable insights. Key … ML models for protein structure, drug-target interactions, and biomarker discovery. Build data pipelines for large biomedical datasets (genomics, clinical, molecular). Implement deep learning models (e.g., CNNs, RNNs, transformers) for biological analysis. Apply NLP to process biomedical literature and clinical data. Collaborate with cross-disciplinary teams to ensure More ❯
Experience and Skills Experience in API development and integrating ML models with backend systems. Deep understanding of CI/CD pipelines for ML, including tools like GitLab CI/CD, MLflow, Docker, and ECS. Exposure to ECS, Kubernetes, Terraform, and More ❯