1 to 25 of 28 Remote/Hybrid MLOps Jobs in the North of England

Experience of working with client sponsors, both technical and non-technical, to collaboratively design requirements and build out solutions.* Experience of designing and implementing MLOPs strategy and framework and proven track record in designing and delivering AI/ML solutions at scale, from concept to production.* Deep understanding of Generative ...

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 ...

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 ...

measurable outcomes. Nice to Have Experience with Bayesian modelling, optimisation algorithms or multi-armed bandits. Exposure to Generative AI, LLMs or agentic AI systems. MLOps experience, including CI/CD, model monitoring and deployment pipelines. Experience working within insurance, fintech, travel, ecommerce or other highly transactional environments. What ...

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/ ...

Prefect.* **Data Quality and Lineage** Familiarity with tools and techniques for data testing, documentation and lineage. Examples include Great Expectations or dbt.* **AI and MLOps** Understanding of how to operationalise machine learning models in production, including model packaging, monitoring and controlled deployment.* **Containerisation and Kubernetes** Confidence deploying applications in containerised ...

threat-intelligence vocabularies. GenAI and GraphRAG : LLM-based extraction, retrieval orchestration, agent/tool integration, prompt design, evaluation, grounding, guardrails, explainability, and evidence traceability. MLOps and observability: Experiment tracking, model versioning, deployment, monitoring, drift and quality checks, auditability, access controls, secrets management, and cost/performance management. Security Knowledge Graph ...

ability to work effectively across technical and business teams. Passion for innovation, continuous improvement and emerging data technologies. Desirable Experience with Scala. Exposure to MLOps, feature stores and machine learning platforms. Our Benefits Hybrid working - 2 days in the office and 3 days working from home 25 days annual leave ...

internal stakeholders.** *Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices.** *Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment.** *Experience of appropriate version control and environment management (such as venvs or Docker).** *Experience of writing technical project ...

cases that cement and enhance this belief and deliver a positive impact in the world. Interested? The Fuzzy Labs team are experts on MLOps and in this publication we're going to tell you WTF it is, and why it is essential for building AI applications #J-18808-Ljbffr ...

Code (IaC) to support data pipelines and processing workflows on AWS. Design and maintain systems for data version control and reproducible machine learning workflows (MLOps). Work closely with data scientists, analysts and engineers to translate analytical and operational requirements into effective data solutions. Contribute to a collaborative, multidisciplinary environment ...

generation (RAG) architectures and agent frameworks such as Google ADK and LangChain, helping transform how the Bank serves customers and empowers colleagues. Data engineering, MLOps and intelligent automation, creating resilient data pipelines, scalable deployment architectures and automated machine learning workflows using contemporary engineering and CI/CD practices, enabling … learning AI literacy Ensemble methods & model optimisation Databases & big data Neural networks & deep learning LLM foundations, engineering, customisation and integration Generative and Agentic AI MLOps & cloud computing Your personal learning plan could include Up to three Stanford Artificial Intelligence Professional Programmes Google Cloud certifications Coursera courses on everything from advanced ...

generation (RAG) architectures and agent frameworks such as Google ADK and LangChain, helping transform how the Bank serves customers and empowers colleagues. Data engineering, MLOps and intelligent automation, creating resilient data pipelines, scalable deployment architectures and automated machine learning workflows using contemporary engineering and CI/CD practices, enabling … learning AI literacy Ensemble methods & model optimisation Databases & big data Neural networks & deep learning LLM foundations, engineering, customisation and integration Generative and Agentic AI MLOps & cloud computing It's all live lectures, tutor-led group work and real-world challenges from day one. Learn it. Apply it. Keep going Your ...

develop expertise across a range of software engineering disciplines, including front-end development, site reliability engineering, data engineering, solutions architecture, machine learning operations (MLOps), user experience (UX), Agile delivery and cloud engineering. You’ll also benefit from mentoring, coaching and collaboration with experienced engineers, helping you broaden your technical knowledge ...

generation (RAG) architectures and agent frameworks such as Google ADK and LangChain, helping transform how the Bank serves customers and empowers colleagues. Data engineering, MLOps and intelligent automation , creating resilient data pipelines, scalable deployment architectures and automated machine learning workflows using contemporary engineering and CI/CD practices, enabling … machine learning AI literacy Ensemble methods & model optimisation Databases & big data Neural networks & deep learning LLM foundations, engineering,customisationand integration Generative and Agentic AI MLOps& cloud computing It’sall live lectures, tutor-led groupworkand real-world challenges from day one. Learn it. Apply it. Keep going Your personal learning plan ...

Head of Engineering and Technical Architect Cloud & Platform Integration: Partner closely with our GCP and Data Engineering teams to build seamless LLMOps/MLOps CI/CD pipelines, ensuring scalable and cost‐effective model deployment via Vertex AI and containerized environments. Take ownership of building and maintaining robust LLMOps pipelines. … data warehouse architectures. Hands‐on experience with Google Cloud Platform (GCP) services including Vertex AI, BigQuery, Cloud SQL, and Google Cloud Storage (GCS). MLOps/LLMOps Pipelines: Proven track record of architecting pipelines for model deployment, performance tracking, hyperparameter tuning, and containerized workflows using Docker and Kubernetes (GKE/ ...

design, build, and operate the infrastructure that enterprise AI and Generative AI workloads run on: the platform layer beneath LLMs, agents, and MLOps pipelines. This spans GPU-accelerated compute and container platforms, model serving and gateway infrastructure, evaluation and guardrail systems, and the MLOps/LLMOps tooling that takes … operate core AI platform components: model serving and gateway infrastructure, agent orchestration and tool-calling frameworks, evaluation harnesses, and guardrail/governance layers• Implement MLOps and LLMOps pipelines (model deployment, monitoring, retraining, and fine-tuning where relevant) using Infrastructure-as-Code, GitOps, and CI/CD• Establish observability, security ...

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 … DevOps, Jenkins, CircleCI etc.) - Experience building LLM or foundation-model applications using frameworks such as LangChain, vector databases or agentic AI approaches - Experience with MLOps and Infrastructure as Code (Terraform, CloudFormation etc.) for data, analytics and AI services - Experience with data reporting and visualisation tools (Power BI, Tableau, Qlik etc. ...

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 … DevOps, Jenkins, CircleCI etc.) - Experience building LLM or foundation-model applications using frameworks such as LangChain, vector databases or agentic AI approaches - Experience with MLOps and Infrastructure as Code (Terraform, CloudFormation etc.) for data, analytics and AI services - Experience with data reporting and visualisation tools (Power BI, Tableau, Qlik etc. ...

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 … DevOps, Jenkins, CircleCI etc.) - Experience building LLM or foundation-model applications using frameworks such as LangChain, vector databases or agentic AI approaches - Experience with MLOps and Infrastructure as Code (Terraform, CloudFormation etc.) for data, analytics and AI services - Experience with data reporting and visualisation tools (Power BI, Tableau, Qlik etc. ...

deploy scalable solutions that drive real business value. You will master Python, SQL and cloud platforms, work on generative AI, AI governance and MLOps, gaining hands-on experience across fraud detection, credit risk and customer analytics in a supportive, ethics-first environment. #J-18808-Ljbffr ...

seeking an AI Platform & Site Reliability Engineering Managing Consultant to design, build and scale secure AI platforms. You will integrate SRE, observability and MLOps, guiding senior clients from strategy to delivery. This role offers flexible hybrid working across Manchester, Glasgow or London, with leadership of multidisciplinary teams and governance shaping ...

Analysis: Apply established data science and machine learning techniques to analyse data and solve business problems under the guidance of senior team members. Production & MLOps: Build, test, and help deploy machine learning models into production environments. Contribute to the design and maintenance of MLOps pipelines to ensure solutions are scalable ...

This job is with Capgemini, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. CAPGEMINI INVENT At Capgemini Invent, we ...

Junior DevOps/MLOps Engineer We are looking for a Junior DevOps/MLOps Engineer to help build, automate and maintain the infrastructure and pipelines that deliver software and machine learning models into production. Working alongside software and AI engineers, you will support reliable deployments, improve automation and help ensure …/CD tool. Linux administration and Docker containers. Infrastructure as code, such as Terraform or AWS CloudFormation. Exposure to model versioning, experiment tracking or MLOps tools. Experience using GitHub Copilot. What You Will Contribute You will help create repeatable deployment processes, reduce manual work and improve the reliability of software ...