The post holder will assist with the successful development and deployment of Machine Learning models that will reside within the D&A platform. Forming part of the D&A development team the ML Ops Engineer will develop, deploy and support machine learning models.
Work alongside data scientists, data engineers and domain experts to collect requirements and establish project goals and document the processes Study and transform data science prototypes, applying the appropriate machine learning algorithms and tools appropriate training to junior team members to ensure all components are delivered in line with Data & Analytics Standards Implement and optimise machine learning algorithms using programming languages such as Python, and Scala Utilise machine learning libraries and frameworks such as PyTorch, ONNX, and XGBoost Evaluate model performance, conduct A/B testing, and iteratively improve model accuracy and efficiency Implement machine learning models in production environments and oversee their performance using relevant metrics Implement MLOps best practiceses to improve the development, deployment and monitoring of ML models. Provide advice and guidance on ML best practices. Document machine learning processes, methodologies, and results to facilitate knowledge sharing and collaboration Stay current with the most recent developments in machine learning research, methodologies, and technologies, integrating them seamlessly into our workflow.
Knowledge:
Proven experience as a machine learning engineer, data scientist, or a similar role A comprehensive grasp of machine learning methodologies and principles, encompassing supervised and unsupervised learning, deep learning, and reinforcement learning. Experience deploying computer vision models is particularly desirable Experience with data manipulation, preprocessing, and feature engineering techniques Experience building Machine Learning solutions for scalable, reliable deployments. Experience developing testing regimes for machine learning systems, including unit, integration, and performance testing. Experience automating the monitoring and evaluation of machine learning systems including data and model drift. Familiarity with data structures, Datamodelling, and software architecture. Experience designing and implementing cloud solutions and ability to build MlOps Pipelines on Azure Cloud.
Key skills:
vel expertise in the Python programming language including PySpark,. Proficiency in utilising machine learning libraries and frameworks like PyTorch, ONNX, and XGBoost Strong understanding of software testing and CI/CD principles and version control (Git, MLFlow) for automated deployment of machine learning systems. Familiarity with our systems (Azure cloud platform covering Azure DevOps Pipelines, Azure Functions, AzureML, Azure Databricks, CosmosDB) is desirable. Excellent problem-solving skills and analytical thinking Strong communication and collaboration skills.
Robert Walters Operations Limited is an employment business and employment agency and welcomes applications from all candidates