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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, data modelling, 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
