151 to 175 of 196 MLOps Jobs in the UK

model lifecycle: deployment, monitoring, evaluation, retraining. Partner with Product, Digital, Marketing, and Operations to shape high‐value use cases. Drive best‐practice engineering and MLOps standards. Requirements Strong experience in ML engineering, AI engineering, or applied data science. Proven track record deploying AI/ML solutions into production. Expertise with … frameworks (scikit‐learn, XGBoost, PyTorch, TensorFlow, LightGBM). Solid experience with LLMs, prompt engineering, RAG, and evaluation. Strong software engineering and MLOps skills (CI/CD, containers, monitoring, model registries). Background in personalisation, recommendation systems, optimisation, CRM/marketing analytics, or conversational AI is beneficial. Please note: this role ...

reporting teams. Work closely with stakeholders across Data, Product, and Leadership to translate requirements into robust data solutions. Support the organisation's move toward MLOps-ready platforms and processes. Your Skills and Experience You will be required to have experience in the following tools: Strong commercial experience building and maintaining … working with occasional monthly travel. A chance to shape a greenfield data platform in a growing tech function. Opportunities for progression across Data Engineering, MLOps, and DevOps practices. How to Apply If this sounds like the next step in your data engineering career, please apply with your ...

optimized architectures for data processing, feature engineering, model training, and inference pipelines. Establish standards, patterns, and best practices for platform components including Lakehouse architecture, MLOps, and data governance. Platform Engineering Architect and guide implementation of Databricks workspace setup, clusters, Unity Catalog, Delta Lake, workflows, and model serving. Lead the integration … Step Functions, CloudWatch, and networking components. Ensure platform scalability, reliability, observability, and high availability. Oversee IAM policies, security controls, and data protection mechanisms. MLOps & AI Capabilities Define architecture for end-to-end ML lifecycle, including model development, experiment tracking, CI/CD, deployment, and monitoring. Evaluate technologies and frameworks ...

resource plans, timelines, and risk frameworks 🏗 Design AI Architectures Translate requirements into scalable AI/ML solutions Design architectures covering: Model development Data pipelines MLOps and monitoring Cloud integration (Azure, AWS, or GCP) Validate feasibility with engineering and delivery teams ✍️ Lead Tender & Bid Responses Own technical sections of AI RFPs … capability in scoping AI/ML programmes and estimating effort Deep understanding of: Machine learning (supervised & unsupervised) Generative AI & LLMs Embeddings, vector databases, RAG MLOps and model lifecycle management Experience with platforms such as: Azure ML, AWS SageMaker, Google Vertex AI Databricks, LangChain, Hugging Face Ability to develop architecture artefacts ...

backtesting under realistic execution constraints. You know why naive train/test splits are dangerous in time series and what to do about it. MLOps & Productionisation. Experience taking models from notebook to production: experiment tracking (MLflow, W&B), model versioning, feature stores, drift detection, and retraining triggers. You can build … input into tooling choices: experiment tracking, feature stores, deployment infrastructure. We have strong engineering support and ship on AWS, but we're building the MLOps layer on the go and you'll help define it. We use AI coding tools - Cursor and Claude Code - as part of the daily workflow ...

Machine Learning Engineer (MLOps) Location: Oxfordshire, UK Permanent HYBRID 3 days per week onsite ARCA Resourcing is partnering with an innovative, established but scaling technology company in Oxfordshire to recruit a Machine Learning Engineer (MLOps). This role offers the opportunity to work at the forefront of advanced computing … Computer Science, Mathematics, Statistics, Physics, or a related field Experience deploying machine learning models to edge or embedded compute hardware Experience with MLOps workflows, including continuous training, testing, and deployment pipelines Experience with real-time systems, sensor data processing, or advanced signal processing Exposure to quantum technologies, quantum information science ...

continuous improvement. Enable Others: Share expertise and help make AI approachable, enabling teams across the organisation to enhance their work with AI. Lead in MLOps & Cloud Infrastructure: Build robust pipelines for model training, deployment, monitoring, and retraining using AWS and modern MLOps best practices. Champion Innovation: Stay ahead of emerging … APIs, microservices, and cloud-native applications. Modern AI Tooling: Familiarity with emerging AI development tools such as Cursor and Gemini is highly desirable. Cloud & MLOps: Practical experience deploying AI solutions on AWS, including CI/CD, model versioning, observability, and retraining pipelines. Data Fluency: Skilled in working with structured ...

model reliability. Apply best practices in model evaluation, mitigating data leakage, and managing the bias/variance trade-off. Deploy and monitor models using MLOps approaches (Docker, CI/CD, cloud platforms like AWS/Azure/GCP). Collaborate closely with engineering and product teams to integrate ML solutions … model development, training, validation, and optimization. Proven experience deploying and maintaining production ML models. Hands-on experience with cloud platforms (AWS, Azure, GCP) and MLOps practices. Demonstrated ability to work with complex real-world datasets and perform feature engineering. Familiarity with modern ML frameworks and libraries, including PyTorch, TensorFlow, HuggingFace ...

model reliability. Apply best practices in model evaluation, mitigating data leakage, and managing the bias/variance trade-off. Deploy and monitor models using MLOps approaches (Docker, CI/CD, cloud platforms like AWS/Azure/GCP). Collaborate closely with engineering and product teams to integrate ML solutions … model development, training, validation, and optimization. Proven experience deploying and maintaining production ML models. Hands-on experience with cloud platforms (AWS, Azure, GCP) and MLOps practices. Demonstrated ability to work with complex real-world datasets and perform feature engineering. Familiarity with modern ML frameworks and libraries, including PyTorch, TensorFlow, HuggingFace ...

Role Summary We are seeking an experienced MLOps Engineer to join our team, focusing on the deployment, monitoring, and maintenance of machine learning models in production environments. This role does not involve model development or end-user support but is critical to ensuring the reliability and performance ...

Lead AI Engineer £80,000 - £90,000 Sheffield (Hybrid, 1-2 days a week) A rare opportunity to step into a Lead level role where you will shape a new AI function and play a ...

role in transforming and modernising the organisation’s machine learning platform. This role involves collaborating across the business to define and implement MLOps best practices, as well as designing, building, and maintaining the infrastructure required for developing and deploying machine learning models. This is initially a 6 month contract with … machine learning models into production systems, driving innovation and operational excellence within the client. Responsibilities: Contribute to the design and the development of robust MLOps, and Agentic Ops frameworks that will enhance our capabilities and drive value across the company. Take offline models data scientists build and turn them into ...

across both software development and infrastructure. You'll enjoy solving complex technical challenges, working in dynamic environments, and collaborating closely with Data Scientists and MLOps teams. A pragmatic, adaptable mindset is key, along with a passion for building scalable, secure systems that enable data-driven outcomes. You should also … data management initiatives Develop, test and deploy new platform capabilities Troubleshoot and enhance existing analytics services Provide hands-on support to Data Scientists and MLOps teams Tackle complex engineering challenges across a varied tech stack Requirements: Strong experience with Python Experience with Kubernetes and Docker Understanding of CI/ ...

ownership: Make decisions that move the whole company forward. We value autonomy, speed, and impact. Stack: Build with modern tools — Python, FastAPI, TypeScript, LLMs, MLOps What We’re Looking For 2+ years of software development experience Proven track record of building and shipping full-stack products in fast-paced, product … driven teams Hands-on experience building production AI systems with Python, PyTorch, and LLMs (OpenAI, Anthropic, etc.), integrated into real user workflows Familiarity with MLOps tools and CI/CD for both traditional and ML-driven systems Strong backend and API development skills - comfortable owning systems end-to-end, from ...

This is a fantastic opportunity to work as an MLOps Engineer on a remote basis, outside IR35, for a major pharmaceutical company. The key skills required for this MLOps Engineer position are: MLOps Image data AWS PyTorch, TensorFlow, JAX If you do have the relevant experience for this long term … remote contract MLOps Engineer role, outside IR35, please do apply. ...

through APIs Working with unstructured data to extract insights and build robust data pipelines Evaluating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating … through APIs Working with unstructured data to extract insights and build robust data pipelines valuating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating ...

through APIs Working with unstructured data to extract insights and build robust data pipelines Evaluating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating … through APIs Working with unstructured data to extract insights and build robust data pipelines valuating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating ...

through APIs Working with unstructured data to extract insights and build robust data pipelines Evaluating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating … through APIs Working with unstructured data to extract insights and build robust data pipelines valuating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating ...

through APIs Working with unstructured data to extract insights and build robust data pipelines Evaluating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating … through APIs Working with unstructured data to extract insights and build robust data pipelines valuating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating ...

through APIs Working with unstructured data to extract insights and build robust data pipelines Evaluating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating … through APIs Working with unstructured data to extract insights and build robust data pipelines valuating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating ...

through APIs Working with unstructured data to extract insights and build robust data pipelines Evaluating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating … through APIs Working with unstructured data to extract insights and build robust data pipelines valuating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating ...

through APIs Working with unstructured data to extract insights and build robust data pipelines Evaluating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating … through APIs Working with unstructured data to extract insights and build robust data pipelines valuating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating ...

through APIs Working with unstructured data to extract insights and build robust data pipelines Evaluating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating … through APIs Working with unstructured data to extract insights and build robust data pipelines valuating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating ...

through APIs Working with unstructured data to extract insights and build robust data pipelines Evaluating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating … through APIs Working with unstructured data to extract insights and build robust data pipelines valuating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating ...

through APIs Working with unstructured data to extract insights and build robust data pipelines Evaluating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating … through APIs Working with unstructured data to extract insights and build robust data pipelines valuating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating ...