7 of 7 MLOps Jobs in Lancashire

Deep technical proficiency with LLMs, NLP, Python, SQL, and major AI/ML frameworks (e.g., PyTorch, TensorFlow). Strong understanding of AI engineering fundamentals including DevOps, CI/CD, MLOps, and DevSecOps. Experience building AI governance frameworks to address ethical risk, model accuracy, and regulatory compliance. Why Join? This is a career-defining opportunity to shape the AI strategy of More ❯

communication and stakeholder engagement skills Desirable: Experience with Delta Lake, Power BI, and Azure DevOps Knowledge of data governance, security, and compliance frameworks Exposure to machine learning workflows and MLOps Relevant certifications (e.g. Microsoft Certified: Azure Data Engineer Associate) Benefits: Competitive salary up to £65,000 Hybrid working (2 days in Manchester office) Pension, private healthcare, and bonus scheme Training More ❯

Ensure compliance, scalability, and reliability of ML systems Skills Required Proven experience with ML in production environments Strong skills in Python, SQL, and AWS (SageMaker, Lambda, etc.) Familiarity with MLOps and real-time data applications A pragmatic mindset and strong problem-solving ability Background in adtech or fraud detection is a bonus More ❯

practices: CI/CD, automated testing, observability. Experience with multi-modal AI (e.g. layout understanding, VLMs, agentic workflows). Comfortable prototyping quickly (Streamlit, Dash) to test ideas. Familiar with MLOps tools like MLflow and model monitoring. Strong communicator who can work across teams. More ❯

will use your skills to: Tune machine learning methods to best leverage our state-of-the-art processing capabilities Deploy and maintain machine learning methods in a DevOps/MLOps based machine learning environment Create robust high-quality code using test-driven development (TDD) techniques and adhering to the SOLID coding standards Your work will enable sustained improvements to products … Head of Data Science, and Head of Technical Underwriting Propose, proof-of-concept, develop, and deliver novel machine learning processes that automate current manual processes, and leverage DevOps and MLOps software. Work in a collaborative environment with data science to help deploy machine learning methods that are state-of-the-art, robust, and future extensible. Tune machine learning methods for … of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in DevOps and Azure ML, or other MLOps and ML Lifecycle technology stacks, such as AWS, Databricks, Google Cloud, etc. Experience with deploying services in Docker and Kubernetes Experience in creating production grade coding and SOLID programming principles More ❯

and model performance Work in a fast-paced start-up culture where your ideas and input matter Skills Strong background in Python and software engineering principles Hands-on with MLOps tools (MLflow, Kubeflow, SageMaker, or similar) Experience with CI/CD (Jenkins, GitLab, Argo, or similar) Familiarity with cloud platforms (AWS, GCP, or Azure) Solid understanding of Docker, Kubernetes, Terraform More ❯

Tesco, Sainsbury’s, O2, Halifax, AA, Saga and Lloyds Bank to list a few. As a Machine Learning Engineer, you will help build and maintain the pricing team’s MLOps and ML Lifecycle environment to support the creation of pipelines by automating the sophisticated machine learning models and processes that underpin our market-leading technical modelling and pricing function. Key … Responsibilities: Build an MLOps/DevOps environment to support machine learning automation Build the pipelines that automate the regular model update and monitoring processes Build a framework that supports the creation, deployment, maintenance, and monitoring elements that non-data scientist and machine learning analysts produce, including assisting with hyper-parameter tuning, feature engineering, feature selection, and validation, reporting and visualisation … and communication processes. Work closely with the data science team to integrate modelling approaches and techniques Key Skills and Experience: Previous experience as a DevOps/MLOps engineer Experience in Azure ML or databricks, or similar industry approved technology stack (i.e. AWS, Kubernetes and Docker, Google Cloud) Understanding of machine learning models and the modelling process, from data ingestion and More ❯