2 of 2 MLOps Jobs in Berkshire

seek an adept expert to contribute significantly to our R&D team, bridging machine learning engineering with applied data science. You'll improve and manage our Machine Learning Operations (MLOps) on Azure, and participate in creating, assessing, and advancing various machine learning models and AI systems. Collaborate extensively with scientific and operational teams to guarantee the robustness, scalability, and reliability … informed decision-making and boost innovation. Help our CDMO's mission by turning research insights into practical solutions efficiently. Key responsibilities: Compose, construct, and uphold resilient machine learning operations (MLOps) pipelines that facilitate the complete lifecycle of AI modelsfrom creation to implementation and supervision. Guarantee the successful deployment of machine learning and large language models (LLMs) in practical operational settings … interpret, share, and act on. Key requirements: MSc or BSc in Computer Science, Data Science, Bioinformatics, Engineering, or a related field, or equivalent experience. Proven experience designing and deploying MLOps pipelines (MLflow, Azure ML, Azure DevOps etc). Strong programming skills in Python and familiarity with common ML/AI libraries (scikit-learn, tensorflow, Keras etc.). Experience implementing machine More ❯

Role? Shape and deliver the security architecture strategy for enterprise cloud and AI/ML programmes. Work on cutting-edge initiatives in the financial services domain, integrating AI and MLOps with security guardrails. Act as a trusted advisor to senior leadership , influencing both business and technology direction. Key Responsibilities Define and evolve security architecture strategies for cloud, AI/ML … and MLOps environments . Act as a senior security advisor to leadership, engineering, and business stakeholders. Develop security architecture standards, patterns, and guidelines for enterprise solutions, with specific coverage for AI/ML workloads. Conduct security architecture reviews, threat modelling, and risk assessments for AI/ML systems and pipelines . Ensure solutions comply with European financial services regulations (GDPR … PSD2, DORA, NIS2) as well as emerging AI governance frameworks (e.g., EU AI Act, NIST AI RMF). Integrate security into DevSecOps and MLOps pipelines , including CI/CD and infrastructure-as-code environments. Drive adoption of Zero Trust principles, encryption standards, IAM policies, and network/data/application security controls. Collaborate with data scientists, ML engineers, and IT More ❯