176 to 200 of 807 MLOps Jobs in the UK

projects and deployments of AI systems. Provide guidance and mentoring to other team members on best practices in AI engineering. Use best practices (e.g., MLOps, AIOps) to improve products/services and processes related to AI. Optimise existing model serving and data pipelines to meet changing performance and security requirements. ...

Specialist Team). The impact you will have Lead the architectural design of production-grade ML workloads on our unified platform, encompassing the entire MLOps lifecycle from end-to-end pipeline creation and optimization (training/inference) to seamless integration with cloud-native services. Provide advanced technical support ...

facing digital products, ideally in banking, fintech, or other regulated industries. Exposure to AI/ML platforms, model-serving environments, GPU-enabled infrastructure, or MLOps practices. Familiarity with security, compliance, and governance expectations in enterprise software environments. Experience contributing to platform modernization, developer experience initiatives, or multi-product engineering environments. ...

experience with distributed computing with Apache SparkTM and knowledge of Spark runtime internals Familiarity with CI/CD for production deployments Working knowledge of MLOps, ML/AI models and AI APIs Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines ...

equivalent work experience. Preferred Skills: Experience with Azure, AWS, GCP, OpenAI, Anthropic, Mistral, Google/Gemini, Databricks, Snowflake, vector databases, orchestration frameworks, and MLOps/LLMOps tooling.Experience supporting large pursuits, proposal development, pricing reviews, or delivery mobilization.AI/ML, cloud, data platform, architecture, or security certifications.Strong analytical thinking, commercial judgment ...

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 ...

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 ...

such as PyTorch or TensorFlow. Industry experience in researching or applying machine learning, especially if in recommender systems, ranking or personalisation Good understanding of MLOps and infrastructure concepts: CI/CD for ML, feature stores, model serving, observability, and versioning. Familiarity with containerisation and cloud‐native environments (e.g. Docker, Kubernetes ...

technical design and architecture for data‐science‐enabled applications, ensuring solutions are maintainable, supportable, observable and easy to operate. Productionise delivery with DevOps and MLOps, automating deployment in AWS and putting evaluation, monitoring and provider‐routing controls in place so AI outputs remain reliable and cost‐effective. Scale practical ...

Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns. Experience in fine-tuning LLMs for domain-specific enterprise applications. Strong expertise in MLOps and LLMOps, ensuring scalable, reliable, and monitorable model deployments. Experience with agentic frameworks and autonomous agent architectures. Proficiency in Python and modern software development practices ...

framework such as PyTorch or TensorFlow.Industry experience in researching or applying machine learning, especially if in recommender systems, ranking or personalisationGood understanding of MLOps and infrastructure concepts: CI/CD for ML, feature stores, model serving, observability, and versioning.Familiarity with containerisation and cloud-native environments (e.g. Docker, Kubernetes, GCP).Familiarity ...

customers and 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 proposals.Experience ...

aspects of generative AI, collaborating with digital, platform, and governance stakeholders.Deploy and Scale AI SolutionsDrive model deployment activities, including containerization, testing, performance monitoring, and MLOps processes.Help utilise cloud platforms (AWS, Azure, GCP) for scalable data science and generative AI deployments.Work with engineers to support the deployment of machine‐learning algorithms ...

support the following: Digital sovereignty Compute optimisation Cost optimisation This role will touch on many elements, including data platforms, AI architecture, cloud architecture, MLOPs, integration frameworks, DevOps processes. You will work closely with the BA and Lead Consultant to make strategic recommendations. With the As-Is architecture you will work ...

decision-making and customer experience, applying patterns such as RAG, orchestration and multi-agent workflows, and tool/function calling.Establish best practices for LLMOps, MLOps and AIOps, including evaluation, observability, model routing, cost and latency optimisation, and secure deployment.Lead the development of reusable AI accelerators, patterns and reference architectures ...

launch, demonstrating mastery of system-level trade-offs. Technical Mentorship: Track record of mentoring more junior engineers and cultivating best practices in AI Engineering, MLOps and software engineering. Problem Definition: Exceptional ability to identify high-value opportunities and translate them into clear, technically feasible plans, securing buy-in from technical ...

TensorFlow/PyTorch, and AWS services. You will work on multi-agent architectures, prompt engineering, and managing data pipelines, with exposure to LangChain and MLOps practices. #J-18808-Ljbffr ...

Deep expertise in LLMs, RAG architectures, Prompt Engineering and Generative AI frameworks such as LangChain or LangGraph Hands-on experience with Python, PyTorch, TensorFlow, MLOps/LLMOps and cloud platforms (Azure, AWS or GCP) Experience deploying AI solutions within government, defence, healthcare or other high-assurance environments Strong understanding ...

Deep expertise in LLMs, RAG architectures, Prompt Engineering and Generative AI frameworks such as LangChain or LangGraph Hands-on experience with Python, PyTorch, TensorFlow, MLOps/LLMOps and cloud platforms (Azure, AWS or GCP) Experience deploying AI solutions within government, defence, healthcare or other high-assurance environments Strong understanding ...

Cluster management Unity Catalog Preferred Skills Databricks Certified DataEngineer Professional/Databricks Certified Architect. Experience with: MLflow Databricks Machine Learning Feature Store Model deployment MLOps Knowledge of streamingtechnologies: Structured Streaming Kafka Experience with datagovernance, compliance,and enterprise securityframeworks. Key Competencies Strong Databricks architectureand implementation expertise. Ability to designscalableand cost-efficientLakehouse ...

engineering foundations, including version control, automated testing, and monitoring; Nice to have: Experience with agentic AI systems, GenAI and LLM systems in production, MCP, MLOps pipelines, real-time or streaming systems. Условия Competitive salary and company bonus scheme; Group pension scheme; Group healthcare and life assurance scheme; Hybrid working environment ...

Skills:Professional certifications in AWS, Azure, GCP, or Data Engineering.Experience within aerospace, defence, manufacturing, or highly regulated industries.Knowledge of AI/ML platforms and MLOps practices.Experience with graph databases and knowledge engineering solutions.Experience implementing data mesh or data fabric architectures.Enterprise Architecture experience.Experience leading large-scale data modernisation programmes.Knowledge of defence ...

Nice to haveExperience in one or more of our domains (assessment/psychometrics, workforce skills/ontologies, recommendations, fraud detection).Familiarity with MLOps practices (CI/CD for ML, experiment tracking, data/version control) in a cloud environment.How we work at PearsonPurpose‐driven, learner‐first; we prize curiosity, decency ...

paths, or platform engineering tooling. Experience with security automation, policy-as-code, cost optimization, or FinOps practices in cloud environments. Exposure to AI infrastructure,MLOps, data pipelines, or supporting engineering teams that build AI-enabled products. Working Locations Croatia, Zagreb - Hybrid Croatia, Pula - Hybrid UK - Remote Why Join Us? Join ...