151 to 175 of 182 MLOps Jobs in the UK

preprocessing, augmentation, and validation workflows. Run structured experiments, evaluate model performance, and iterate based on measurable results Build, deploy, and operate end-to-end MLOps pipelines, including experiment tracking, model versioning, and production monitoring. Package and deploy models using Docker and cloud infrastructure, with a focus on reliability and scalability … familiarity with the Hugging Face ecosystem Experience with audio or speech models and frameworks. Experience building and maintaining end-to-end ML pipelines and MLOps tooling (e.g. MLflow, Weights & Biases, DVC, or similar). Strong Python skills; experience with Docker, CI/CD, and cloud platforms (Azure preferred) Practical experience ...

Lead Engineer page is loaded## Lead Engineerlocations: UK - Hooktime type: Full timeposted on: Posted Todayjob requisition id: R0025434**At Elanco (NYSE: ELAN) – it all starts with animals!****As a global leader in animal health, we ...

As a Lead Engineer, you will be part of our Enterprise AI engineering team to deliver secure, reliable, and innovative AI solutions across our business. In this role, you’ll be responsible for advancing our ...

doing Develop and implement machine learning models and pipelines Work with structured and unstructured data at scale Deploy models into secure production environments Support MLOps practices including CI/CD for ML systems Optimise models for performance, accuracy, and reliability Work closely with stakeholders to translate requirements into technical solutions … deployment Experience with Python and ML frameworks (e.g. TensorFlow, PyTorch, scikit-learn) Familiarity with data pipelines and cloud or on-prem environments Understanding of MLOps principles Ability to work in secure or regulated environments Eligibility Must be eligible for DV Security Clearance (5+ years UK residency required) Package ...

strategy. Designing, building, and productionising ML pipelines aligned to business goals. Delivering NLP and LLM-driven solutions, including fine-tuning and deployment. Implementing strong MLOps practices across model training, deployment, and monitoring. Working closely with Data Scientists to support, maintain, and improve models in production. Building APIs and data products … pipelines. Hands-on experience with Databricks and Azure. Practical experience with NLP and LLMs, including fine-tuning and applied use cases. Solid understanding of MLOps, CI/CD for ML, and production model monitoring. Exeperience with stakeholders and translating business problems into technical solutions. Experience building or integrating APIs, such ...

strategy. Designing, building, and productionising ML pipelines aligned to business goals. Delivering NLP and LLM-driven solutions, including fine-tuning and deployment. Implementing strong MLOps practices across model training, deployment, and monitoring. Working closely with Data Scientists to support, maintain, and improve models in production. Building APIs and data products … pipelines. Hands-on experience with Databricks and Azure. Practical experience with NLP and LLMs, including fine-tuning and applied use cases. Solid understanding of MLOps, CI/CD for ML, and production model monitoring. Exeperience with stakeholders and translating business problems into technical solutions. Experience building or integrating APIs, such ...

strategy. Designing, building, and productionising ML pipelines aligned to business goals. Delivering NLP and LLM-driven solutions, including fine-tuning and deployment. Implementing strong MLOps practices across model training, deployment, and monitoring. Working closely with Data Scientists to support, maintain, and improve models in production. Building APIs and data products … pipelines. Hands-on experience with Databricks and Azure. Practical experience with NLP and LLMs, including fine-tuning and applied use cases. Solid understanding of MLOps, CI/CD for ML, and production model monitoring. Exeperience with stakeholders and translating business problems into technical solutions. Experience building or integrating APIs, such ...

strategy. Designing, building, and productionising ML pipelines aligned to business goals. Delivering NLP and LLM-driven solutions, including fine-tuning and deployment. Implementing strong MLOps practices across model training, deployment, and monitoring. Working closely with Data Scientists to support, maintain, and improve models in production. Building APIs and data products … pipelines. Hands-on experience with Databricks and Azure. Practical experience with NLP and LLMs, including fine-tuning and applied use cases. Solid understanding of MLOps, CI/CD for ML, and production model monitoring. Exeperience with stakeholders and translating business problems into technical solutions. Experience building or integrating APIs, such ...

strategy. Designing, building, and productionising ML pipelines aligned to business goals. Delivering NLP and LLM-driven solutions, including fine-tuning and deployment. Implementing strong MLOps practices across model training, deployment, and monitoring. Working closely with Data Scientists to support, maintain, and improve models in production. Building APIs and data products … pipelines. Hands-on experience with Databricks and Azure. Practical experience with NLP and LLMs, including fine-tuning and applied use cases. Solid understanding of MLOps, CI/CD for ML, and production model monitoring. Exeperience with stakeholders and translating business problems into technical solutions. Experience building or integrating APIs, such ...

strategy. Designing, building, and productionising ML pipelines aligned to business goals. Delivering NLP and LLM-driven solutions, including fine-tuning and deployment. Implementing strong MLOps practices across model training, deployment, and monitoring. Working closely with Data Scientists to support, maintain, and improve models in production. Building APIs and data products … pipelines. Hands-on experience with Databricks and Azure. Practical experience with NLP and LLMs, including fine-tuning and applied use cases. Solid understanding of MLOps, CI/CD for ML, and production model monitoring. Exeperience with stakeholders and translating business problems into technical solutions. Experience building or integrating APIs, such ...

ideation through deployment and monitoring, working closely with Data Engineers, Analysts, Product, Risk, and Technology stakeholders. They will set standards for experimentation, governance, and MLOps while mentoring and developing other data scientists within the function. This is a hands-on technical leadership role - both strategic and delivery-focused. The Role … leading other data scientists. Desirable • Experience in credit risk, fraud detection, affordability modelling, or payments analytics.• Familiarity with model risk management frameworks.• Exposure to MLOps tooling (CI/CD pipelines, automated testing, model registries).• Experience with model explainability techniques (e.g., SHAP, LIME).• Experience shaping data science roadmaps ...

Establish a scalable AI runtime environment to support rapid prototyping and early deployment of LLM agents and agentic workflows.* Design and implement a robust MLOps stack with model versioning, CI/CD pipelines, and automated monitoring for operational resilience.* Build secure, compliant AI development and deployment architectures while aligning with … Qualifications:*** Proven leadership in designing scalable, cloud-native or hybrid AI/ML platforms that support experimentation and secure enterprise deployment.* Deep expertise in MLOps strategy and execution, including end-to-end pipelines, CI/CD, model versioning, and retraining workflows.* Hands-on experience with model deployment and runtime management ...

underpins AI and machine learning delivery . This is a hands-on senior platform role , focused on building robust, Kubernetes-based platforms that enable MLOps engineers, ML engineers, and data scientists to deploy, run, and manage models safely and effectively in production. While you'll need a strong understanding … just running clusters. You will: Design, build, and operate a Kubernetes-based platform that supports multiple ML and engineering teams Extend Kubernetes with MLOps-specific capabilities , rather than treating it as a finished product Provideplatform-level support for: Model development and experimentation Model packaging, deployment, and promotion Scalable inference ...

Implements infrastructure as code using Terraform, including network, security, and compute resources. Supports Airflow as part of platform orchestration. Collaborates closely with Data Engineers, MLOps Engineers, and Solution Architects to ensure the infrastructure and pipelines meet performance, scalability, and compliance requirements. Follows best practices for platform security, auditing, and cost … using Azure Key Vault and Azure AD. Ensure connectivity between on-prem services and Azure cloud infrastructure using GreenLink and hybrid networking. Collaborate with MLOps and Data Engineers to ensure reproducible, reliable, and auditable infrastructure across environments. Monitor system health, logging, and metrics using platform observability tools (e.g. Azure Monitor ...

experimentation with A/B and Multi-armed bandit testing frameworks, power analysis, variance reduction, and online-offline alignment.* Work together with Data Engineering, MLOps, and Game Tech teams to guarantee dependable data foundations, feature accessibility, and model deployment pathways.* Build internal data products to improve the speed and quality … problem definition to production deployment and monitoring.* Demonstrated proficiency in clustering, predictive modeling, reinforcement learning, and Bayesian statistics.* Hands-on experience in software engineering, MLOps, and deploying machine learning models at scale.* Proficiency in SQL, Python, and familiarity with big data technologies (e.g., Kafka, Spark) and/or cloud platforms ...

customer outcomes with the autonomy to make decisions that surprise and delight our customers. Contribute full‐stack development including software engineering, DevOps, and MLOps, along with light task and project management to ensure your AI solutions deliver maximum value. We are looking for someone who is as excited about Unitary … have: Experience working in a fully remote, international team Previous startup experience A background in building and operating agentic AI systems Experience with MLOps practices and tools, and monitoring machine learning systems in production Knowledge of CI/CD practices and tools such as GitLab CI, Argo CD Proficiency with ...

Senior/Lead Machine Learning Engineer - Time-Series, Pricing, Customer Behaviour, Feature stores, MLOps London Hybrid | £100,000 – £120,000 + Equity This is a genuinely interesting opportunity for someone who enjoys solving large-scale, real-world machine learning problems rather than purely experimental work. The team is building forecasting … hybrid with two days per week onsite in London. Experience around forecasting, time-series modelling, recommendation systems, production ML infrastructure, or large-scale MLOps environments would all be highly relevant. Salary: £100,000 - £120,000 plus equity and benefits. APPLY NOW for immediate consideration. N.B. - They do not offer visa ...

hiring for - Senior MLOps/Python Cloud Engineer job location : London UK Job Type : Permanent job details: We are hiring a Senior MLOps/Python Cloud Engineer The project centres on building a next-generation parametric pricing engine taking a robust Python prototype and transforming it into a production-grade … decisions Strong communication skills confident explaining technical decisions to non-technical stakeholders good to have : Background in insurance, financial services, or another regulated industry MLOps or model deployment experience Familiarity with Power Apps or low-code platforms ...

Lead AI Engineer (Python LLM MLOps) London/WFH to £125k Are you an experienced Software Engineer with a strong knowledge of AI, LLMs and agentic coding? You could be progressing your career at a global finance technology consultancy, working with clients including global Investment Banks and financial services organisations. … About you: You have hands-on experience deploying LLMs and multi-modal models at scale in production You have a strong understanding of scalable MLOps, observability and cloud-native AI deployment You have strong Python coding skills and API development skills You're collaborative and pragmatic with advanced stakeholder communication ...

Financial Services, Asset Management , or a similarly regulated industry. Technical Proficiency: Hands-on experience with Data Lakes/Warehouses (e.g., Snowflake), Feature Stores, and MLOps concepts. Data Literacy: Ability to perform data profiling and analysis using SQL and Python to drive product decisions. Communication: Exceptional ability to influence a diverse … related field (Master's preferred). Technical Skills Required Data Tools: SQL, Python, Snowflake/Databricks, Tableau/Power BI. Frameworks: Agile/Scrum, MLOps, Data Governance, Metadata Management. Integration: API design, event-driven architecture, and data modeling. Randstad Technologies is acting as an Employment Business in relation to this ...

infrastructure using Microsoft Azure technologies including Azure AI Foundry, Azure OpenAI, Azure ML and Copilot Studio. Develop and manage CI/CD, LLMOps, and MLOps pipelines for Generative AI applications. Design and deploy GenAI, RAG and intelligent agent solutions across enterprise systems. Implement Infrastructure as Code (Terraform) and secure cloud … infrastructure engineering. Hands-on expertise with Generative AI, RAG architectures, NLP and agentic workflows. Experience building secure CI/CD, LLMOps, and MLOps pipelines. Knowledge of Terraform, cloud security, APIs, and enterprise integrations. Familiarity with frameworks such as LangChain or Semantic Kernel. Strong stakeholder communication and cross-functional collaboration skills. ...

looking for a Lead Platform Engineer to join a growing engineering organisation and play a pivotal role in designing, building, and operating an MLOps platform that enables AI and data science teams to deliver reliably in production. This is a senior, hands-on technical leadership role , not a people-management … based workloads safely and at scale . The focus is not simply on running Kubernetes clusters - it's on layering real MLOps capability on top of Kubernetes to create a platform that is usable, supportable, and trusted in live environments. What you'll be doing ...

estate supports scalable analytics/AI (reliable pipelines, governance, standards, metadata, lineage). Drive simplification and interoperability across fragmented systems and spreadsheets. AI Delivery & MLOps Build repeatable delivery capability (product-based delivery, agile ways of working, MLOps, model monitoring). Partner with Technology/Engineering teams to deploy models into … case portfolio, deliver at pace, and embed solutions operationally. Strong grasp of modern data stack principles (cloud data platforms, integration, governance, MDM, analytics engineering, MLOps). Excellent commercial storytelling—able to engage a PE board and translate technical delivery into value. ...

within a multidisciplinary data team, partnering with data engineers, architects, and analysts to design, build, and productionise machine-learning models using modern Python and MLOps practices across secure cloud environments. Key Requirements Active Security Clearance (SC) - must be current and transferable Proven experience as a Data Scientist in central government … Strong hands-on experience with Python for data science and machine learning Solid understanding of machine-learning techniques (supervised, unsupervised, model evaluation) Experience with MLOps practices, including: Model versioning and deployment CI/CD for ML workflows Monitoring and performance management Experience working with cloud-based data platforms ...

making the function known Team Building Scale the team in line with what the roadmap demands – hiring across ML engineering, data science, and MLOps Develop the existing team, create career paths, and set technical and cultural standards What the First Year Looks Like 3 months: DS roadmap defined cross‐functionally … external presence. 12 months: DS is a recognised, embedded function with a track record of delivery. Experimentation is a working discipline used beyond DS. MLOps maturity has stepped up. The team has grown in line with what was needed to get here. What You Bring Must‐Haves 4‐5 years ...