DXC Technology is committed to building diverse, inclusive teams. We welcome applications from all backgrounds and particularly encourage interest from women, underrepresented groups, and neurodivergent candidates. We offer reasonable adjustments throughout the hiring process and are dedicated to creating a supportive, accessible environment for everyone. Machine Learning Ops Engineer Location: Erskine, Newcastle, Farnborough or London Candidates must be eligible for clearance Are you passionate about bringing machine learning solutions into real-world production environments? Do you enjoy collaborating with others to build scalable, reliable systems? We are looking for a Machine Learning Ops Engineer to join our growing team. This role is ideal for someone who enjoys solving complex problems, working cross-functionally, and continuously developing their technical expertise in a supportive environment. If you dont meet every single requirement listed below, we still encourage you to apply. We value potential, curiosity, and a willingness to learn. Key Responsibilities Deploying, monitoring, and scaling machine learning models in production. Collaborating with data scientists, engineers, and stakeholders to integrate AI solutions into scalable products. Supporting the full ML lifecycle, from experimentation to deployment and optimisation. Applying best practices in data engineering and contributing to architectural decisions. Using modern MLOps tools and CI/CD approaches to improve reliability and efficiency. Contributing to a culture of knowledge-sharing and continuous improvement. Key Skills & Experience Strong Python skills and familiarity with ML libraries such as Pandas, NumPy, and scikit-learn. Experience with frameworks such as TensorFlow, Keras, or PyTorch. Exposure to gradient boosting tools such as XGBoost, LightGBM, or CatBoost. Experience with model deployment tools (e.g., ONNX, TensorRT, TensorFlow Serving, TorchServe). Familiarity with ML lifecycle tools such as MLflow, Kubeflow, or Azure ML Pipelines. Experience working with distributed data processing (e.g., PySpark) and SQL. Understanding of software engineering best practices, including version control (Git). Knowledge of CI/CD principles in ML environments. Experience with cloud-native ML platforms is advantageous. Why Join Us Be part of a cutting-edge AI communitydriving digital transformation across the UK&I. Work at the intersection of business innovation and emerging AI technologies. Opportunity to shape the future of AI adoptionwithin some of the UKs most impactful industries. Collaborative, forward-thinking environment with continuous learning and development opportunities.