Description
Location: Fully Remote UK
Job Type: 6-Month Contract with the possibility of extension
Interview Process: Remote video interviews
Rate: DOE, Outside IR35
A leading London-based FinTech firm is seeking a talented and motivated Azure ML Engineer with experience in the financial sector to join their team.
Key Responsibilities:
- Collaborate with Data Science and Innovation teams to design, develop, and deploy AI models within an Azure ML environment.
- Lead deployment and infrastructure activities, ensuring seamless integration of AI solutions into Azure-based FinTech systems.
- Manage large-scale data processing using Azure Data Services, optimising datasets for machine learning applications.
- Develop and optimise ML and Generative AI models, ensuring efficient deployment on Azure Machine Learning and Azure Cognitive Services.
- Deploy, monitor, and maintain AI models in Azure-based production environments, leveraging Azure ML Ops for automation and performance tracking.
- Build and maintain scalable AI pipelines using Azure Databricks, Azure Synapse Analytics, and Azure Functions for end-to-end AI solution deployment.
- Enhance AI model performance through rigorous testing, tuning, and continuous monitoring within Azure ML infrastructure.
- Work closely with stakeholders to align AI initiatives with Azure cloud best practices, regulatory compliance, and FinTech industry standards.
- Stay up to date with advancements in AI, ML, and GenAI, with a focus on innovations within Azure’s AI ecosystem.
Key Skills:
- Azure ML & Cloud Migration Expertise: Extensive hands-on experience in configuring,migrating,and deploying ML models from on-prem Kubeflow/TensorFlow stacks to fully managedAzureML solutions utilizingAzureMachineLearning ,Databricks ,andCognitiveServices.AzureMLCertification is highly desirable.
- AI/ML Solution Development inAzure: Proven abilityto design ,implement ,andoptimiseAI/MLmodelswithinAzureenvironments ,withastrongfocusonfinancialapplications suchasriskmodelling,frauddetection,recommendationsystems,andNLPforfinancialdata.
- AdvancedDataScience&AzureEngineeringSkills: Expertiseinmachinelearning ,statistics ,experimentaldesign,andmodelvalidation ,withdeepproficiencyinPythonandAzureMLtechstack,includ ingAzureDatabricks,SynapseAnalytics,andAzureFunctions.
- AzureOptimisedDataHandling: Strongexperienceindatapreprocessing ,featureengineering,andmanagingbothstructuredandunstructuredfinancialdatasetswithinA zureDataServices.
- MachineLearning&GenerativeAIonAzure: In-depthknowledgeofsupervised,unsignedlearning,andGenerativeAImethodologies,w ithhands-on expertiseindeployingAImodelsatscaleusingAz ureAIservices.
- Analytical&Cloud-FocusedProblemSolving: Strongproblem-solvingability ,analyticalmindset,andattentiontodetail ensuringAISolutionsarescalable,e fficient,andfullyintegratedwithinAz ure .
- EffectiveCommunication&CollaborationinAZureEcosystem : Abilitytocollaborateina fast-pacedFinTechenvironment aligningAIinitiativeswithAz urebestpractices regulatoryrequirementsandindustrystandards.
If you’re a skilled engineerwithapassionforapplyingyourexpertiseintheFinTechindustry,we’d love to hearfromyou—applytoday!