426 to 450 of 635 MLOps Jobs in the UK

agentic technologies, end‐to‐end. Skills and Experience Proven leadership experience in Gen AI delivery Hands‐on technical understanding of modern AI tooling, MLOps, and model deployment and generative/agentic AI frameworks Commercial mindset, experience bringing AI, including generative, use cases into production Strong communication skills and the ability ...

image classification, object detection and segmentation tasks. Experience creating clear documentation and annotation guidelines. Excellent organisational skills. Desirable Experience with PyTorch datasets. Experience with MLOps or data pipelines. Understanding of computer vision model training. Knowledge of active learning workflows. Experience with Git. Robotics or autonomous systems experience. What ...

/UX and graphical/web design Nice to Have Experience with Python or Rust Familiarity with SQL Exposure to DevOps practices Experience with MLOps or AI infrastructure What they will be looking for: Problem Solver - You love solving challenging problems (proven history of doing so) Ownership & Intensity - You take ...

image classification, object detection and segmentation tasks. Experience creating clear documentation and annotation guidelines. Excellent organisational skills. Desirable Experience with PyTorch datasets. Experience with MLOps or data pipelines. Understanding of computer vision model training. Knowledge of active learning workflows. Experience with Git. Robotics or autonomous systems experience. What ...

Purview, Azure ML, Databricks, MLflow or Microsoft Fabric . Knowledge of DAMA-DMBOK, NIST AI RMF, ISO 23894, ISO 27001 or UK GDPR . MLOps, model monitoring or AI risk/control experience. Benefits: Salary up to £80,000 25 days holiday + bank holidays Private Medical Insurance Hybrid working ...

image based AI models, density and object-based identification o Experience with AI/ML platforms and processes: OpenVINO or similar toolkit; MLOps training pipeline; SageMaker. Requires experience of data governance, privacy policies and AI assurance methods Requires indepth AWS experience, particularly S3, serverless computing (Lambda), EventBridge/SNS/ ...

master the stack from pytorch based learning libraries to complex data networking and GPU utilisation. We're looking for an experienced AI Infrastructure or MLOps Engineer who has already built and operated production AI systems rather than someone at the beginning of their career. You'll have strong experience with ...

production efficiency and latency requirements; Write clean, well‐tested and well‐documented code and uphold engineering standards across the team; Lead model handovers to MLOps engineers with documentation covering capabilities, known limitations, failure modes and retraining criteria; Stay current with advances in ML engineering, distributed training and biomedical AI tooling. ...

every project. Strong communication skills: you'll need to challenge stakeholder expectations sometimes, not just relay them. Bonus points: experience establishing ML engineering/MLOps best practice from scratch, background in regulated or enterprise environments, or a track record of driving reuse through shared frameworks and tooling. Why join ...

opportunities. Deep expertise across enterprise data domains, including data strategy, governance, privacy, analytics and AI transformation. Strong understanding of data science, AI, Generative AI, MLOps, business intelligence, responsible AI, AI governance and modern analytics operating models, with the ability to translate emerging technologies into business value. Proven experience leading complex ...

organisations. Previous consulting or advisory experience within a professional services environment at Principal Consultant or equivalent level. Familiarity with AI governance, model risk management, MLOps, responsible AI frameworks, or regulatory considerations relating to AI deployment. Experience building senior client relationships, contributing to business development activities, or supporting proposition and capability ...

senior member of the AI Enablement leadership team, contributing to the team's overall direction alongside the Senior Staff Data Engineer and Senior Staff MLOps Engineer. This is a unique opportunity to be part of a critical strategic initiative for a pharmaceutical company that invests heavily in research and development ...

engineering standards. Design and run large-scale distributed training on multi-node GPU clusters; drive throughput, stability, and cost efficiency in partnership with MLOps & Data Platform teams. Define what pretraining-scale data looks like: partner with the Data Collection team and external data providers to secure a steady supply ...

senior member of the AI Enablement leadership team, contributing to the team's overall direction alongside the Senior Staff Data Engineer and Senior Staff MLOps Engineer. This is a unique opportunity to be part of a critical strategic initiative for a pharmaceutical company that invests heavily in research and development ...

cases (forecasting, ATP optimisation, document AI, anomaly detection). Define ML data contracts and embed models in operational processes (Fiori, SAC). Establish MLOps foundations: pipelines, CI/CD, monitoring, retraining, drift. Chair the Data & AI Design Authority, driving alignment across internal teams and multiple SI/vendor partners. Govern ...

ensure evaluation methods are reliable, identify gaps, and drive new methodology for evaluating our models. Stay up to date with the latest in MLOps practices and tools and bring improvements into the workflow. About you In order to set you up for success as a Staff Machine Learning ...

core levers (telecoms, ISP, utilities, media, fintech or insurance) Working knowledge of modern data stacks and ML delivery (data lakes and warehouses, feature pipelines, MLOps, CDPs, decisioning platforms) sufficient to shape scope and challenge trade-offs with engineers and scientists Telecoms or ISP experience, and/or experience ...

applications using Generative AI, Large Language Models and orchestration frameworks. Write high-quality Python code and contribute to cloud-native applications and services. Apply MLOps best practices, including CI/CD, containerisation, monitoring and observability. Partner with data scientists, engineers and business stakeholders to translate business challenges into impactful … orchestration frameworks. Strong Python programming skills and understanding of modern backend architectures. Experience working with cloud platforms and production-grade AI systems. Knowledge of MLOps, CI/CD, containerisation and model monitoring. Experience building data pipelines for model training, fine-tuning and inference. Solid grounding in machine learning, statistics ...

agentic workflow capabilities for legal content products. In addition to writing code on complex systems, this position provides technical direction on architecture, MLOps, responsible AI, legacy system integration, AWS-based delivery, and AI-assisted development practices. The position does not have direct reports. Key Responsibilities Serve as the initial point … accuracy, groundedness, citation quality, hallucination risk, agent task success, latency, cost, reliability, and business value. Successfully implement development processes, coding best practices, code reviews, MLOps practices, and responsible AI controls. Apply AI-assisted development tools to reduce software development cycle time and support code explanation, test generation, refactoring, debugging, documentation ...

agentic workflow capabilities for legal content products. In addition to writing code on complex systems, this position provides technical direction on architecture, MLOps, responsible AI, legacy system integration, AWS-based delivery, and AI-assisted development practices. The position does not have direct reports. Key Responsibilities: Serve as the initial point … accuracy, groundedness, citation quality, hallucination risk, agent task success, latency, cost, reliability, and business value. Successfully implement development processes, coding best practices, code reviews, MLOps practices, and responsible AI controls. Apply AI-assisted development tools to reduce software development cycle time and support code explanation, test generation, refactoring, debugging, documentation ...

build, testing, deployment, monitoring and handover. This is a senior, hands‐on delivery role for someone who can work independently across architecture, integration, DevOps, MLOps, AIOps, data engineering and governance. You will make technical decisions, solve complex integration challenges and ensure AI solutions are reliable, scalable and safe … Landing Zone sandbox to test technical options, demonstrate value and provide clear go/no-go recommendations before full delivery. DevOps, MLOps and AIOps ownership: Implement and maintain CI/CD, monitor and release pipelines using Azure DevOps, including version control, rollback capability, automated testing and production health monitoring. Documentation ...

experiments (A/B testing, causal inference) to validate impact and guide decision making. Cross-functional delivery: Partner closely with Product, Engineering, and MLOps teams to move ideas from prototype into scalable production systems. Mentorship: Support and coach junior data scientists on technical approach, code quality, and best practice, without … function approaches tooling, methodology, and model governance. Technical Environment Languages/Tools: Python (NumPy, Pandas, Scikit learn), deep learning frameworks (PyTorch/TensorFlow), SQL. MLOps: MLflow, cloud ML platforms (Azure ML, AWS SageMaker, or Databricks). Focus areas: Predictive modelling, recommender systems/personalisation, and increasingly, applied LLM/GenAI ...

applications on the Databricks Data Intelligence Platform. You will also continue to sharpen your technical expertise in cutting‐edge areas like GenAI, ML, MLOps, and LLMOps, while mentoring colleagues and establishing yourself as an AI thought leader. Impact you will have Architecting Workloads: Design and implement production-level … workloads, including end‐to‐end pipelines, training/inference optimization, MLOps lifecycle management, and integration with cloud‐native services. GenAI Leadership: Serve as a practitioner for enterprise GenAI solutions, specializing in RAG architectures, agentic systems (including tool‐calling, multi‐agent orchestration, and guardrails), AI observability, and natural language querying ...

applications on the Databricks Data Intelligence Platform. You will also continue to sharpen your technical expertise in cutting-edge areas like GenAI, ML, MLOps, and LLMOps, while mentoring colleagues and establishing yourself as an AI thought leader. Impact you will haveArchitecting Workloads: Design and implement production-level … workloads, including end-to-end pipelines, training/inference optimization, MLOps lifecycle management, and integration with cloud-native services. GenAI Leadership: Serve as a practitioner for enterprise GenAI solutions, specializing in RAG architectures, agentic systems (including tool-calling, multi-agent orchestration, and guardrails), AI observability, and natural language querying ...

Customer Analytics, Marketing Analytics, Customer Lifetime Value, Churn Prediction, Demand Forecasting, Stock Forecasting, Production Machine Learning, Cloud Data Platforms, Data Products, Git, Version Control, MLOps, Data Pipelines. Location: Hybrid role. 2 days per week in office Either: Welwyn Garden City, Hertfordshire or Slough, Berkshire Type: Permanent | Full-Time Overview: @mecscomms … Data integration & modelling * Stakeholder management * Agile delivery experience Desirable: * MLflow * PyTorch * Databricks Asset Bundles * Graph Databases * Azure Machine Learning * GitHub Actions * CI/CD * MLOps * Marketing Analytics * Customer Lifetime Value (CLV) * Churn Prediction * Retail Analytics * Customer Personalisation * Decision Intelligence Key Traits: * Curious & analytical * Commercially minded * Customer focused * Strong statistical thinking ...