25 of 25 MLOps Jobs in the North West

with call/contact-centre analytics, Microsoft Teams Graph API, or telephony platforms (BroadWorks, Webex Calling). Knowledge of data governance, model ethics, and MLOps practices. Exposure to data visualization and predictive analytics for customer-experience metrics. Advanced degree in AI, ML, Data Science, or related discipline. ISTQB AI Testing ...

with call/contact-centre analytics, Microsoft Teams Graph API, or telephony platforms (BroadWorks, Webex Calling). Knowledge of data governance, model ethics, and MLOps practices. Exposure to data visualization and predictive analytics for customer-experience metrics. Advanced degree in AI, ML, Data Science, or related discipline. ISTQB AI Testing ...

with call/contact-centre analytics, Microsoft Teams Graph API, or telephony platforms (BroadWorks, Webex Calling). Knowledge of data governance, model ethics, and MLOps practices. Exposure to data visualization and predictive analytics for customer-experience metrics. Advanced degree in AI, ML, Data Science, or related discipline. ISTQB AI Testing ...

with call/contact-centre analytics, Microsoft Teams Graph API, or telephony platforms (BroadWorks, Webex Calling). Knowledge of data governance, model ethics, and MLOps practices. Exposure to data visualization and predictive analytics for customer-experience metrics. Advanced degree in AI, ML, Data Science, or related discipline. ISTQB AI Testing ...

Collaborate with software engineers to integrate models into live applications Monitor, evaluate, and improve model performance over time Contribute to best practice around MLOps, automation, and model governance Document solutions clearly for both technical and non-technical stakeholders Essential Skills and Experience Commercial experience as a Machine Learning Engineer ...

essential: Proficiency in Arcade scripting across ESRI runtime environments. Familiarity with the Microsoft Azure cloud platform, including data and AI services, and MLOps Knowledge of geospatial data warehousing and analytics. Familiarity with leading AI/ML platforms and libraries Experience building and scheduling ETL workflows. Knowledge of spatial data management ...

influence stakeholders Clear, pragmatic communicator with a delivery-focused mindset Desirable (Not Essential) Experience with PyTorch, TensorFlow, or similar ML frameworks Exposure to MLOps, model monitoring, or AI performance optimisation Frontend collaboration experience (e.g. React-based systems) Cloud-native or containerised deployment experience Why work for us? Lead the development ...

into products and decision-making. Responsibilities Build and maintain end-to-end AI/ML pipelines Develop, deploy and monitor machine learning models Apply MLOps best practices including CI/CD Collaborate with data, analytics and engineering teams Ensure data governance, security and responsible AI Experience Strong experience ...

evaluation of new model architectures. · Implement production features end-to-end under guidance from senior engineers. · Participate in code reviews, testing, deployment, and MLOps workflows. · Work across internal products and contract-based venture projects. Requirements · Strong foundational programming skills in Python. · Basic understanding of AI/ML models ...

evaluation of new model architectures. · Implement production features end-to-end under guidance from senior engineers. · Participate in code reviews, testing, deployment, and MLOps workflows. · Work across internal products and contract-based venture projects. Requirements · Strong foundational programming skills in Python. · Basic understanding of AI/ML models ...

evaluation of new model architectures. · Implement production features end-to-end under guidance from senior engineers. · Participate in code reviews, testing, deployment, and MLOps workflows. · Work across internal products and contract-based venture projects. Requirements · Strong foundational programming skills in Python. · Basic understanding of AI/ML models ...

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

willing to work from the Manchester office 3 days per week Nice to have Experience with Azure or AWS ML tooling Experience with MLOps CI/CD and model monitoring Experience building AI features into customer-facing products Why this role £550 per day outside IR35 Real production AI work ...

maintain scalable, end‐to‐end AI/ML pipelines using Microsoft Fabric Develop, train, deploy and monitor machine learning and deep learning models Implement MLOps best practices including versioned data and features, CI/CD pipelines, model promotion and rollback. Collaborate with data scientists, analytics engineers, product managers and software … generation Knowledge of AutoML, hyperparameter optimisation and advanced MLflow features. Experience working with streaming or real‐time data platforms Familiarity with CI/CD, MLOps and deployment pipelines (Azure DevOps, GitHub Actions, Docker). Commercial exposure to e‐commerce, travel or holiday‐lettings environments. Experience mentoring others or leading technical ...

maintain scalable, end‐to‐end AI/ML pipelines using Microsoft Fabric Develop, train, deploy and monitor machine learning and deep learning models Implement MLOps best practices including versioned data and features, CI/CD pipelines , model promotion and rollback . Collaborate with data scientists, analytics engineers, product managers … generation Knowledge of AutoML, hyperparameter optimisation and advanced MLflow features. Experience working with streaming or real‐time data platforms Familiarity with CI/CD, MLOps and deployment pipelines (Azure DevOps, GitHub Actions, Docker). Commercial exposure to e‐commerce, travel or holiday‐lettings environments. Experience mentoring others or leading technical ...

frameworks (e.g., LangGraph, PydanticAI) and managing memory and tool-calling in production. Engineering Mindset: Ability to write clean, testable Python and familiarity with modern MLOps stacks. Product Experience: Experience shipping ML systems in production for real users, with an experimental mindset and high bar for AI ethics. Why Join Wilgot ...

using Azure Key Vault and Azure AD. Ensure connectivity between on-prem services and Azure cloud infrastructure using GreenLink and hybrid networking. Collaborate with MLOps and Data Engineers to ensure reproducible, reliable, and auditable infrastructure across environments. Monitor system health, logging, and metrics using platform observability tools (e.g. Azure Monitor ...

production deployment — while mentoring top engineers and collaborating closely with research and infrastructure leaders. You'll combine technical depth in deep learning and MLOps with leadership in execution and strategy, ensuring that Turing's AI initiatives deliver reliable, high-performance systems that translate research breakthroughs into measurable business impact. This … navigating the intersection of research, engineering, and product delivery. Roles & Responsibilities: Lead and mentor a cross-functional team of ML engineers, data scientists, and MLOps professionals. Oversee the full lifecycle of LLM and ML projects — from data collection to training, evaluation, and deployment. Collaborate with Research, Product, and Infrastructure teams ...

teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support model monitoring, drift detection, and ongoing optimisation Required Experience Proven commercial experience as a Machine Learning Engineer … with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35 ...

teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support model monitoring, drift detection, and ongoing optimisation Required Experience Proven commercial experience as a Machine Learning Engineer … with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35 ...

Collaborate with product and engineering to integrate ML systems into user-facing features Develop and deploy production-quality machine learning frameworks, while maintaining robust MLOps pipelines Stay up-to-date with the latest advancements in AI, conduct research, and explore innovative techniques Influence key decisions on architecture and implementation … including latency, token cost control, context window constraints, monitoring and prompt versioning Strong Python skills and experience with PyTorch, TensorFlow or Keras Exposure to MLOps practices and hands-on experience with Sagemaker and/or Vertex AI Bachelor's degree in a technical field such as computer science or years ...

ML Engineer Location: Chester (Hybrid - 2x week in office) Salary: £70,000 - £80,000 About the Role I'm working with an established company who are looking to bring an ML Engineer into their team. ...