1 to 25 of 32 Remote/Hybrid MLOps Jobs in the North of England

.Experience building and deploying Generative AI solutions, including prompt engineering, fine-tuning, and evaluation of large language models (LLMs) or other generative architectures.Understanding of MLOps principles, including automated model training, CI/CD for ML, model versioning, monitoring, and retraining.Experience deploying AI and GenAI solutions on cloud platforms (AWS, Azure ...

Computer Science, Machine Learning, or related field Nice to Have Published research in top ML venues (NeurIPS, ICML, ACL, CVPR). Experience with MLOps tools: MLflow, Weights & Biases, DVC. Familiarity with distributed training frameworks (DeepSpeed, Horovod). Experience with LLM fine-tuning and prompt engineering. Contributions to open-source ...

frameworks (eg LangChain/LlamaIndex-style tooling, multi-agent patterns) - Prompt engineering and systematic evaluation/guardrail tooling (hallucination detection, safety testing) - LLMOps/MLOps - model versioning, deployment, monitoring, and rollback for AI services in production - Cloud-native engineering across major providers (AWS, Azure, or GCP), including their AI/ ...

Intelligence, Data Science, or a related technology discipline Minimum 2:1 degree classification (or equivalent) Desirable Azure OpenAI, AWS Bedrock and Google Gemini experience MLOps, Data Engineering or Platform Engineering experience Experience leading technical teams Knowledge of Agentic AI, AI Agents and emerging AI frameworks What's On Offer? Opportunity ...

Hands-on experience in developing and deploying AI solutions in a professional setting.Experience building data pipelines and working with structured and unstructured data.Experience with MLOps tools and best practices for model deployment, monitoring, and governance.Experience working in Agile delivery environments.Strong analytical and problem-solving skills, with attention to detail.Programming: Strong ...

equivalent platforms.Developing high-quality, maintainable code and working with software engineering practices such as version control, testing, code review and CI/CD.Working with MLOps or workflow tools such as MLflow, Kubeflow, Argo or equivalent frameworks.Scaling models or analytical services for enterprise or operational use.Applying statistical methods, model evaluation techniques ...

generative AI and the modern AI stack, including large language models, prompt engineering, retrieval-augmented generation (RAG), vector databases, evaluation/monitoring and MLOps principles, with the ability to shape investment cases and operating models at scale.Extensive experience providing executive oversight for production AI delivery (you steer architecture and engineering ...

generative AI and the modern AI stack, including large language models, prompt engineering, retrieval-augmented generation (RAG), vector databases, evaluation/monitoring and MLOps principles, with the ability to shape investment cases and operating models at scale.Extensive experience providing executive oversight for production AI delivery (you steer architecture and engineering ...

controlStrong collaboration skills, working across engineering, security, data science and product teamsAnd it would be great if you had any of the following...Exposure to MLOps or SMLOps tooling and model lifecycle managementExperience supporting AI/ML pipelines, feature engineering or analytics platformsKnowledge of AI governance and secure adoption of generative ...

controlStrong collaboration skills, working across engineering, security, data science and product teamsAnd it would be great if you had any of the following...Exposure to MLOps or SMLOps tooling and model lifecycle managementExperience supporting AI/ML pipelines, feature engineering or analytics platformsKnowledge of AI governance and secure adoption of generative ...

working with AWS-native data services and event-driven architecturesExperience building data products that support analytics, reporting, machine learning, or AI use casesKnowledge of MLOps, AI Engineering, Agentic AI, or Generative AI implementation patternsExperience leading distributed engineering teamsExperience establishing engineering standards, reusable frameworks, and community-of-practice initiativesKnowledge of data ...

agreed requirements, delivery plans and quality standards.Support the deployment and operationalisation of AI systems, including model monitoring, performance optimisation, CI/CD and MLOps practices.Collaborate with solution architects, data scientists, business analysts and engineers to ensure AI solutions are integrated effectively into wider technology and business environments.Apply responsible AI, security … equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible AI considerations. Understanding of MLOps and production AI practices, including CI/CD, model versioning, monitoring, automated testing, retraining and performance optimisation. Experience using cloud platforms and cloud-native ...

Teams. Strong communication skills and the ability to work with both technical and non-technical stakeholders. Desirable Experience AI governance and responsible AI practices. MLOps or LLMOps environments. Agentic AI frameworks such as LangGraph, CrewAI or AutoGen. AI orchestration tools such as N8N. Data governance and Microsoft Purview. Prompt engineering ...

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 ...

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 ...

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 ...

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 ...