126 to 150 of 306 MLOps Jobs in England

secure‐by‐design Data & AI solutions across cloud environments (Azure‐led, with AWS/GCP awareness). Oversee AI/ML lifecycle delivery, including MLOps and operationalisation. Own programme financial performance including forecasting, margin management and cost control. Support bids and shape delivery approaches for strategic Data & AI opportunities. Requirements ...

looking for: Some experience (academic or project-based) with Python and an understanding of machine‐learning workflows and model evaluation. Interest in MLOps, model governance and responsible AI practices. A highly collaborative working style with a growth mindset. Strong critical thinking and problem‐solving skills. A minimum ...

/CD workflows Knowledge of automated testing methodologies Strong communication and collaboration skills Desirable C++ development experience Embedded Linux exposure Machine learning deployment experience MLOps experience NVIDIA Jetson experience Experience developing software that interfaces with hardware Experience within engineering, instrumentation, industrial technology or related product environments About ...

platforms, AI‐enabled applications or machine learning solutions into production environments Deep understanding of modern AI architecture patterns and real‐world operational delivery, including MLOps/Evals Strong Python engineering capability and experience working across cloud‐native engineering environments Experience integrating AI capabilities into wider enterprise, cloud and data ecosystems ...

successful as an AI Enterprise Architect, you should have experience with: AI/ML Architecture: AI/ML frameworks, multi‐cloud platforms, data architectures, MLOps, and secure, scalable enterprise AI solution design. Enterprise Architecture & Governance: EA frameworks, AI governance, ethical AI, compliance, and alignment to business and IT strategy. Stakeholder ...

enterprise-scale operating models and shared services environments is beneficial. Required Skills AI & Agent Platforms: Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry Data & MLOps: Databricks, Azure SQL, ADLS, Azure AI Search Cloud & Integration: Microsoft Azure, API Management, Containers Identity & Security: Azure Entra ID, Key Vault, RBAC Observability & Governance: Logging ...

your knowledge in this area A solid understanding of software engineering principles, including data pipelines, CI/CD, containerisation and observability, with exposure to MLOps practices and tooling Comfortable providing technical guidance, mentoring and support to a small number of less‐experienced engineers Enjoy collaborating across teams and contributing ...

partnering with Product and Finance to align expected and realized impact Define measurement approaches for AI and algorithmic features in collaboration with Data Science, MLOps and Engineering Shape product and commercial strategy through opportunity identification, impact sizing and evidence-based recommendations Lead high-impact and complex analysis, ensuring outputs ...

organisations solve complex operational, technical and regulatory challenges through AI adoption at scale. You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications. Key responsibilities: Building … Using Python and SQL to build robust, scalable AI and data solutions Working with cloud platforms such as AWS, Azure, GCP or Databricks Supporting MLOps, LLMOps, CI/CD and software engineering best practice Collaborating with technical and non-technical stakeholders across complex programmes Helping identify technical, delivery, security, data ...

organisations solve complex operational, technical and regulatory challenges through AI adoption at scale. You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications. Key responsibilities: Building … Using Python and SQL to build robust, scalable AI and data solutions Working with cloud platforms such as AWS, Azure, GCP or Databricks Supporting MLOps, LLMOps, CI/CD and software engineering best practice Collaborating with technical and non-technical stakeholders across complex programmes Helping identify technical, delivery, security, data ...

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 ...

virtual assistants through advanced prompt engineering and agent orchestration 🔹 Integrate AI applications with SQL, NoSQL, Vector Databases, Knowledge Graphs, and third-party systems 🔹 Implement MLOps best practices and contribute to CI/CD pipelines using Docker, Kubernetes, and Cloud Platforms 🔹 Collaborate with Data Scientists, Architects, Product Managers, and Engineering teams … expertise in: Prompt Engineering Conversational AI NLP Applications AI Agent Development ✔ Experience building scalable APIs using FastAPI ✔ Strong understanding of: HTTP & gRPC Docker & Kubernetes MLOps & AI Deployment Cloud AI Services (AWS, Azure, or GCP) ✔ Experience deploying production-grade AI solutions on enterprise platforms ⭐ Nice to Have ✔ Experience with Vector Databases ...

input validation, secure handling of sensitive data (PII/confidential property information), and protection against prompt injection and other AI-specific vulnerabilities. Collaborate with MLOps and platform engineers to ensure models are deployed, monitored, and iterated in production environments. Maintain clear documentation for AI systems, APIs, and workflows. Stay … frameworks like BentoML or equivalent. Familiarity with vector databases and retrieval pipelines for RAG architectures. Knowledge of cloud platforms (AWS, GCP, Azure) and MLOps tooling (MLflow, Kubeflow, or similar). Familiarity with voice‐to‐text, IVR, and/or computer vision systems is a plus. Strong understanding of software engineering ...

Code CI/CD, automation, and platform reliability Running production workloads with high availability requirements Plus, experience with one or more of the following: MLOps or ML platform engineering RAG architectures, embeddings, or vector search Model serving, observability or performance optimisation Data/AI workflow orchestration in Databricks or similar ...

powered solutions. This role is ideal for a hands-on engineer with strong expertise in Generative AI, Large Language Models (LLMs), Knowledge Graphs, MLOps, and Full-Stack Development . You will play a key role in designing, building, and scaling enterprise-grade AI applications that drive business innovation and deliver … SPARQL . Develop graph-based AI solutions using techniques such as: Graph Neural Networks (GNNs) Link Prediction Node Embeddings Graph Analytics MLOps & AI Operations Implement MLOps best practices for AI model deployment, monitoring, governance, and continuous integration/continuous deployment (CI/CD). Ensure scalability, reliability, security, and performance ...

Perform feature engineering to improve model accuracy Design ML pipelines and automate model deployment Collaborate with software engineers to integrate models into applications Use MLOps practices for monitoring, retraining, and lifecycle management Conduct A/B tests and measure real-world model performance Stay up to date with the latest ...

vulnerability management, and automation A passion for continuous improvement and mentoring others Desirable Experience in defence, aerospace, or other highly regulated sectors Exposure to MLOps, edge computing, or GPU-enabled workloads If this role is of interest, apply now or email your CV to me directly at (url removed ...

production environments API integration, secure deployment patterns, and enterprise data connectivity Experience building and scaling RAG-based architectures and agentic systems Strong understanding of MLOps/LLMOps principles in cloud-native environments Overview of Role Design and deploy enterprise-grade AI agents and copilots embedded into business workflows Build scalable ...

working with data engineers and software teams to move solutions from prototype to supported delivery. Desirable skills and experience Experience with enterprise AI adoption, MLOps, cloud architecture, NLP/LLMs or advanced analytics platforms. Experience managing mixed teams of data scientists, analysts, engineers and product specialists. Experience in client-facing ...

particularly within the YOLO family. Familiarity with model optimization techniques such as quantization and pruning, and deployment frameworks like TensorRT and OpenVINO. Experience with MLOps tools and practices, including version control (Git), Docker, and CI/CD with GitHub Actions. Excellent problem-solving skills and the ability to perform ...

such as SuperSet, Tableau or PowerBI is a bonus) Hands-on experience in machine learning model development, evaluation, and production deployment, with familiarity in MLOps principles to build scalable and standardised workflows and implement effective ML monitoring systems Proven ability to create polished presentations and effectively communicate insights to customers ...

high-performance culture. Structural Excellence: You define how the team works internally. You will structure workflows, set standards for model and code quality and MLOps, and ensure the team is organised for maximum velocity and accountability. All this within the company's Agile methodology. The Candidate: "The Architect & The Doer ...

strong technical architecture.* Drive the transition from experimental AI capabilities to scalable production systems.**What We Are Looking For*** Strong engineering background (ML engineering, MLOps engineer, or equivalent).* Proven experience building complex systems from 0→1.* Ability to independently write production-quality code and build functional prototypes.* Practical experience ...

quality, review processes, and technical governance. ● Build observability, incident management, and on-call practices that scale with team growth and deployment frequency. ● Embed DevOps, MLOps, security, and compliance practices into day-to-day workflows. ● Balance technical debt with feature delivery needs, making trade-offs transparent to the business. Cross-Functional ...

AXA Group is looking for a Machine Learning Engineer to join their Transversal Data team in Bristol. The engineer will play a key role in modernizing the machine learning platform, collaborating closely with cross-functional ...