26 to 50 of 61 MLOps Jobs in the North of England

needed to put machine learning into production at scale. You'll have a meaningful say in how the deployment framework, model registry and wider MLOps capability are built. You won't simply inherit someone else's setup. If you've reached the point where you want to build the systems ...

needed to put machine learning into production at scale. You'll have a meaningful say in how the deployment framework, model registry and wider MLOps capability are built-not simply inherit someone else's setup. If you've reached the point where you want to build the systems behind production ...

Hiscox is seeking an experienced Machine Learning Engineer to join a newly formed ML Engineering team. You will build and maintain infrastructure to deploy data‐driven models, and develop Python APIs to serve ML models ...

including machine learning models, data pipelines and application components that are secure, reliable and performant.Drive the operationalisation of AI solutions using modern engineering and MLOps practices, including CI/CD, model monitoring, testing and lifecycle management.Ensure solutions are developed in line with security, privacy, governance and responsible AI requirements, particularly … practical implementation of model development and deployment.Working knowledge of Generative AI, including large language models, prompt engineering, retrieval-augmented generation and evaluation approaches.Experience with MLOps and modern engineering practices, including CI/CD pipelines, model versioning, monitoring and automated testing.Experience deploying AI solutions on cloud platforms such as Azure ...

that actually make it into production. We're supporting a major financial services organisation as they build a brand-new enterprise Data Platform and MLOps capability . This is a rare opportunity to join at an early stage and play a key role in shaping how Data Science is delivered ...

Event Hubs, or Kinesis for real-time data processing Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines Experience processing and managing unstructured data types (text, images, logs, sensor data) Understanding of Lambda and Kappa architectural patterns and when to apply each ...

growth over the last few years and we’re looking to continue with this momentum as we build on our reputation as Open Source MLOps and applied AI experts, expand our role within the community, and continue to deliver high-quality solutions to our clients. What we’re looking … also enjoy being part of a culture that values: Loving what we do: a real passion for open source, applied AI, MLOps, and taking pride in our work. Just trying it: AI is moving quickly. We love to develop new skills, solve new problems and thrive on a challenge. Being ...

into complex enterprise workflows.Bridge Design & Implementation: Oversee the full technical lifecycle, from selecting the right model architectures to ensuring robust CI/CD and MLOps pipelines.Inference & Infrastructure: Deploy and optimise models using cloud services like AWS Bedrock and Azure AI Foundry, or self-host them on GPU/CPU hardware … Evaluation: Implement frameworks and approaches to evaluate model performance against business objectives, both pre-deployment and on an ongoing basis as part of the MLOps lifecycle.Drive System Performance: Assess and optimise for performance, cost-efficiency, and reliability, ensuring AI outputs meet the rigorous standards required for our Security & Justice clients.System ...

Fuzzy Labs, a Manchester-based tech consultancy, seeks a Lead Applied AI Engineer to guide squads, own client projects from discovery to production, and shape technical direction. You'll mentor engineers, collaborate with customers, and ...

maintain end-to-end AI/ML pipelines in Microsoft Fabric Design, train, deploy, and monitor machine learning and deep learning models Implement MLOps best practices: versioned data & features, CI/CD pipelines, model promotion, and rollback Collaborate with data scientists, analytics engineers, product managers, and developers to turn business … augmented generation Knowledge of AutoML, hyperparameter tuning and advanced MLflow features Experience with streaming and real-time data platforms Familiarity with CI/CD, MLOps and deployment pipelines (Azure DevOps, GitHub Actions, Docker) Commercial awareness in e-commerce, travel or holiday-lettings sectors Experience mentoring others or leading technical workstreams ...

qualification in relevant field (eg Computer Science, Data Science, Operational Research) Experience with modern data platforms (eg Databricks, Snowflake, MS Fabric). Familiarity with MLOps practices and version control tools (e.g. Git). Experience with deployment and maintenance of ML models in production environments. SQL MS Excel Power BI Python ...

solutions are based on sophisticated analytical thought and research. Qualifications & Skills AI/ML Architecture: AI/ML frameworks, multi‐cloud platforms, data architectures, MLOps, and secure, scalable enterprise AI solution design. Enterprise Architecture & Governance: EA frameworks, AI governance, ethical AI, compliance, and alignment to business and IT strategy. Stakeholder ...

workloads on AWS (or multi‐cloud with strong AWS depth).Deep understanding of AI/ML solution patterns (data pipelines, training, inference, monitoring, and MLOps) and how they map onto AWS services (e.g. SageMaker, Batch, Step Functions, EKS/ECS, data lake components).Proven ability to take research and prototype ...

workloads on AWS (or multi‐cloud with strong AWS depth).Deep understanding of AI/ML solution patterns (data pipelines, training, inference, monitoring, and MLOps) and how they map onto AWS services (e.g. SageMaker, Batch, Step Functions, EKS/ECS, data lake components).Proven ability to take research and prototype ...

deploying machine learning solutions into cloud-native production environments Experience with containerisation technologies such as Docker and orchestration platforms including Kubernetes Knowledge of modern MLOps practices including CI/CD, version control (Git) and infrastructure automation Experience working with cloud platforms and modern data ecosystems (Azure and Databricks experience beneficial … solutions in a commercial environment Experience deploying machine learning models within regulated industries such as financial services or insurance Exposure to enterprise-scale MLOps and cloud infrastructure Experience contributing to platform architecture and engineering best practices ...

About AXA: AXA is a global leader in insurance and financial services, dedicated to helping customers protect what matters most to them. As the sixth-largest insurance company in the world, we provide a wide ...

About AXA: AXA is a global leader in insurance and financial services, dedicated to helping customers protect what matters most to them. As the sixth-largest insurance company in the world, we provide a wide ...

architectural expertise across AWS and Azure, alongside experience with modern data platforms such as Snowflake and Databricks. Experience with AI/ML, MLOps and responsible AI is important, as is the ability to operate confidently with both technical teams and senior business stakeholders. We're looking for someone ...

experiments (A/B testing, causal inference) to validate impact and guide decision making. Cross-functional delivery: Partner closely with Product, Engineering, and MLOps teams to move ideas from prototype into scalable production systems. Mentorship: Support and coach junior data scientists on technical approach, code quality, and best practice, without … function approaches tooling, methodology, and model governance. Technical Environment Languages/Tools: Python (NumPy, Pandas, Scikit learn), deep learning frameworks (PyTorch/TensorFlow), SQL. MLOps: MLflow, cloud ML platforms (Azure ML, AWS SageMaker, or Databricks). Focus areas: Predictive modelling, recommender systems/personalisation, and increasingly, applied LLM/GenAI ...

agentic technologies, end‐to‐end. Skills and Experience Proven leadership experience in Gen AI delivery Hands‐on technical understanding of modern AI tooling, MLOps, and model deployment and generative/agentic AI frameworks Commercial mindset, experience bringing AI, including generative, use cases into production Strong communication skills and the ability ...

experiments (A/B testing, causal inference) to validate impact and guide decision making. Cross-functional delivery: Partner closely with Product, Engineering, and MLOps teams to move ideas from prototype into scalable production systems. Mentorship: Support and coach junior data scientists on technical approach, code quality, and best practice, without … function approaches tooling, methodology, and model governance. Technical Environment Languages/Tools: Python (NumPy, Pandas, Scikit learn), deep learning frameworks (PyTorch/TensorFlow), SQL. MLOps: MLflow, cloud ML platforms (Azure ML, AWS SageMaker, or Databricks). Focus areas: Predictive modelling, recommender systems/personalisation, and increasingly, applied LLM/GenAI ...

Engineering: Deep prompt engineering & optimization skills for GenAI.Vector DBs & RAG: Designed solutions using vector DBs & Retrieval Augmented GenAI (RAG) for knowledge applications.GenAI ModelOps/MLOps & Governance: GenAI ModelOps/MLOps knowledge with ethical AI governance focus.Multimodal & Code Generation: Architected GenAI for multimodal (vision, audio, language) & code generation.ER&I GenAI Applications ...

prescriptive models for key use cases such as demand forecasting, optimisation, and anomaly detection in infrastructure projects.Establish best practices for model lifecycle management, including MLOps, monitoring, and retraining, ensuring alignment with AECOM’s global standards.Extract actionable insights from complex datasets to inform strategic decisions across infrastructure, environmental, and urban development … urban development sectors.Strong proficiency in Python (pandas, scikit-learn, PyTorch/TensorFlow) and SQL, with experience in geospatial and environmental data analysis.Experience with MLOps tools (MLflow, Docker, CI/CD pipelines) and cloud platforms (Azure preferred), ensuring scalable and reliable solutions.Proven ability to influence non-technical stakeholders and communicate complex ...

lasting impact.At Credera, you will work on diverse client projects, such as building modern, AI-enabled data platforms on AWS using DevOps and MLOps practices, including large, distributed workloads, batch and streaming pipelines, and the data foundations that power machine learning, Generative AI and Large Language Model solutions. Working with … Azure DevOps, Jenkins, CircleCI etc.)Experience building LLM or foundation-model applications using frameworks such as LangChain, vector databases or agentic AI approachesExperience with MLOps and Infrastructure as Code (Terraform, CloudFormation etc.) for data, analytics and AI servicesExperience with data reporting and visualisation tools (Power BI, Tableau, Qlik etc.)Experience ...

test and deploy machine learning models, analytical pipelines and data science components that are robust, scalable and maintainable.Support the operationalisation of ML solutions through MLOps practices, including model monitoring, versioning, automated testing, CI/CD and performance optimisation.Apply responsible AI, model explainability, security, privacy and governance considerations throughout the development … PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring and optimisation.Understanding of MLOps and production ML practices, including CI/CD, model versioning, automated testing, retraining, monitoring and reproducible delivery.Experience using cloud platforms and data science environments such ...