5 of 5 MLOps Jobs in Lancashire

business requirements into end-to-end AI architectures Lead the design of data pipelines, model training environments, and deployment frameworks Implement best practices for MLOps, CI/CD, and model life cycle management Evaluate and recommend AI tools, platforms, and frameworks Ensure alignment with data governance, security, and regulatory requirements … platforms (Azure, AWS, or GCP) and cloud-native architecture Strong background in data engineering and large-scale data platforms (e.g., Spark, Databricks) Experience implementing MLOps frameworks, including CI/CD and model governance Experience integrating AI into microservices, APIs, and enterprise systems Exposure to advanced AI techniques such ...

experiments and POCs into scalable, reliable services. Develop solutions for large scale unstructured data, including complex document processing and LLM ready data pipelines. Own MLOps practices, covering CI/CD, model serving, observability and lifecycle management. Provide hands on technical leadership, contributing to architecture decisions and best practice. … delivery focused partner to stakeholders, confidently explaining trade offs and recommendations. Your Skills & Experience Strong commercial experience as an ML Engineer or MLOps focused engineer, ideally with a software engineering background. Proven ability to deploy, operate and maintain machine learning systems in production. Hands on experience with cloud based data ...

helping to build out the wider ML function. You'll operate as a hands-on technical leader, setting best practice across ML pipelines, MLOps, and data products while working closely with Data Scientists, Engineers, and senior stakeholders. Key responsibilities include: Leading and championing ML Engineering as a core capability across … organisation Designing, building, and productionising end-to-end ML pipelines aligned to business strategy Implementing robust MLOps processes (CI/CD, model deployment, monitoring, governance) Delivering ML solutions for complex NLP and LLM use cases, including large-scale document processing Collaborating closely with Data Scientists to support model development, fine ...

strategy. Designing, building, and productionising ML pipelines aligned to business goals. Delivering NLP and LLM-driven solutions, including fine-tuning and deployment. Implementing strong MLOps practices across model training, deployment, and monitoring. Working closely with Data Scientists to support, maintain, and improve models in production. Building APIs and data products … pipelines. Hands-on experience with Databricks and Azure. Practical experience with NLP and LLMs, including fine-tuning and applied use cases. Solid understanding of MLOps, CI/CD for ML, and production model monitoring. Exeperience with stakeholders and translating business problems into technical solutions. Experience building or integrating APIs, such ...

ideation through deployment and monitoring, working closely with Data Engineers, Analysts, Product, Risk, and Technology stakeholders. They will set standards for experimentation, governance, and MLOps while mentoring and developing other data scientists within the function. This is a hands-on technical leadership role - both strategic and delivery-focused. The Role … leading other data scientists. Desirable • Experience in credit risk, fraud detection, affordability modelling, or payments analytics.• Familiarity with model risk management frameworks.• Exposure to MLOps tooling (CI/CD pipelines, automated testing, model registries).• Experience with model explainability techniques (e.g., SHAP, LIME).• Experience shaping data science roadmaps ...