15 of 15 Remote/Hybrid MLOps Jobs in the North West

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 ...

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 ...

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 ...

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. ...

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 ...

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 ...

Platform Strategy & Architecture: Assess, define and evolve enterprise AI platform architectures, covering LLM and agentic frameworks, AI gateways, model lifecycle management, data platforms, MLOps/LLMOps foundations and integration patterns. Support clients in evaluating build, buy and hybrid approaches aligned to business needs, risk appetite and operational requirements.• AI Platform … operating cloud-native, platform engineering, AI platform or reliability engineering solutions within complex enterprise environments. • Strong understanding of AI platform architectures including LLMOps, MLOps, agentic AI frameworks, model lifecycle management and AI operational controls. • Experience establishing and scaling SRE practices including observability, SLIs, SLOs, error budgets, incident management and reliability ...

supporting AI/ML workloads. You'll apply deep technical expertise across infrastructure automation, environment provisioning and deployment pipelines , working closely with Data Engineers, MLOps Engineers and Solution Architects to ensure the platform meets performance, scalability, cost and compliance requirements. There is flexibility on base location across … Vault and Azure AD Supporting connectivity between on-prem services and Azure cloud infrastructure (hybrid networking/private connectivity, including GreenLink) Working with MLOps and Data Engineers to ensure environments are reproducible, reliable and auditable across multiple environments Supporting observability and platform health: logging and metrics monitoring using tooling such ...