176 to 200 of 271 MLOps Jobs in the UK excluding London

integrations Fine‐tune, optimize, and deploy large language and multi‐modal models with a focus on scalability, reliability, and low‐latency performance Build scalable MLOps pipelines and cloud‐native AI applications to support secure, production‐grade deployments Collaborate with clients and cross‐functional teams to shape AI engineering strategy … enterprise or large‐scale production environments Strong software engineering expertise in Python, including backend development, API design, and distributed systems Solid understanding of scalable MLOps, observability, CI/CD practices, and cloud‐native AI deployment architectures Excellent communication, stakeholder management, and problem‐solving skills within agile delivery environments Bonus Points ...

Head of Engineering and Technical Architect Cloud & Platform Integration: Partner closely with our GCP and Data Engineering teams to build seamless LLMOps/MLOps CI/CD pipelines, ensuring scalable and cost-effective model deployment via Vertex AI and containerized environments. Take ownership of building and maintaining robust LLMOps pipelines. … data warehouse architectures. Hands-on experience with Google Cloud Platform (GCP) services including Vertex AI, BigQuery, Cloud SQL, and Google Cloud Storage (GCS). MLOps/LLMOps Pipelines: Proven track record of architecting pipelines for model deployment, performance tracking, hyperparameter tuning, and containerized workflows using Docker and Kubernetes (GKE/ ...

About AXA: AXA is a global leader in insurance and financial services, dedicated to helping customers protect what matters most to them. As the sixth-largest insurance company in the world, we provide a wide ...

About AXA: AXA is a global leader in insurance and financial services, dedicated to helping customers protect what matters most to them. As the sixth-largest insurance company in the world, we provide a wide ...

About AXA: AXA is a global leader in insurance and financial services, dedicated to helping customers protect what matters most to them. As the sixth-largest insurance company in the world, we provide a wide ...

About AXA: AXA is a global leader in insurance and financial services, dedicated to helping customers protect what matters most to them. As the sixth-largest insurance company in the world, we provide a wide ...

About AXA: AXA is a global leader in insurance and financial services, dedicated to helping customers protect what matters most to them. As the sixth-largest insurance company in the world, we provide a wide ...

About AXA: AXA is a global leader in insurance and financial services, dedicated to helping customers protect what matters most to them. As the sixth-largest insurance company in the world, we provide a wide ...

About AXA: AXA is a global leader in insurance and financial services, dedicated to helping customers protect what matters most to them. As the sixth-largest insurance company in the world, we provide a wide ...

technical leadership AWS, CI/CD, APIs, containers and modern programming languages Cloud-native engineering, automated testing, observability and infrastructure as code Developer platforms, MLOps, AI automation or agentic workflows Coaching agile teams and influencing technical and non-technical stakeholders The role offers hybrid working within the UK, with onsite ...

technical leadership * AWS, CI/CD, APIs, containers and modern programming languages * Cloud-native engineering, automated testing, observability and infrastructure as code * Developer platforms, MLOps, AI automation or agentic workflows * Coaching agile teams and influencing technical and non-technical stakeholders The role offers hybrid working within the UK, with onsite ...

designs and ensure strong technical architecture.Drive the transition from experimental AI capabilities to scalable production systems.What We Are Looking ForStrong engineering background (ML engineering, MLOps engineer, or equivalent).Proven experience building complex systems from 01.Ability to independently write production-quality code and build functional prototypes.Practical experience with LLM application architectures ...

ensure strong technical architecture. Drive the transition from experimental AI capabilities to scalable production systems. What We Are Looking ForStrong engineering background (ML engineering, MLOps engineer, or equivalent).Proven experience building complex systems from 01.Ability to independently write production-quality code and build functional prototypes. Practical experience with LLM application ...

people considerations.Experience working with data platforms, machine learning workflows, and modern software development practices.Experience with Document Intelligence, AI-powered automation, Agentic AI solutions, DevOps, MLOps, and Responsible AI practices.Preferred QualificationsPrevious experience leading managers, team leads, or highly autonomous technical teams.Experience scaling organizations through periods of growth and organizational transformation.Master ...

Experience working with data platforms, machine learning workflows, and modern software development practices. Experience with Document Intelligence, AI-powered automation, Agentic AI solutions, DevOps, MLOps, and Responsible AI practices. Preferred QualificationsPrevious experience leading managers, team leads, or highly autonomous technical teams. Experience scaling organizations through periods of growth and organizational ...

Earth‐system or environmental services, Copernicus, Destination Earth or machine‐learning‐enabled forecasting workflows, including relevant approaches to reproducibility, model versioning, workflow orchestration or MLOps Languages Candidates must be able to work effectively in English. A good knowledge of one of the Centre’s other working languages (French or German ...

guide the strategy, architecture, and delivery of our next generation Hybrid AI Platform. In this role, you will provide leadership across AI infrastructure, MLOps, cloud native platform engineering, and operational excellence -setting direction for teams that build and run production grade AI/ML platforms on Kubernetes. You will drive … driven, cloud native platform automation using ArgoCD and Helm. Set standards for Linux systems management, platform hardening, and operational reliability across all AI infrastructure. MLOps & Model Lifecycle Management Define and evolve the enterprise MLOps architecture, enabling reproducible, automated, and governed AI model workflows. Lead teams in building and optimizing ...

software code development Builds engineering stack required for Data and AIML products, including data engineering, backend engineering, Cloud infra DevOps and MLOps Designs and implements data engineering solutions, leveraging modern big data technologies Contributes to software engineering communities of practice and events that explore new and emerging technologies Embraces … experience developing Production-scale Cloud-native data engineering solutions in commercial environments Familiarity with Cloud Data engineering services (e.g., ETL, Glue, S3, Athena) and MLOps stack Ability to convey design choices and results clearly and communicate effectively to stakeholders of various backgrounds Preferred qualifications, capabilities, and skills Experience with data ...

Head of Engineering and Technical Architect. Cloud & Platform Integration: Partner closely with our GCP and Data Engineering teams to build seamless LLMOps/MLOps CI/CD pipelines, ensuring scalable and cost-effective model deployment via Vertex AI and containerized environments. Take ownership of building and maintaining robust LLMOps pipelines. … data warehouse architectures. Hands‐on experience with Google Cloud Platform (GCP) services including Vertex AI, BigQuery, Cloud SQL, and Google Cloud Storage (GCS). **MLOps/LLMOps Pipelines:** Proven track record of architecting pipelines for model deployment, performance tracking, hyperparameter tuning, and containerized workflows using Docker and Kubernetes (GKE/ ...

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 ...

designing and building APIs, distributed systems, and event-driven architectures in modern programming languages such as Python, TypeScript, Java, Go, or similar Familiarity with MLOps practices, model monitoring, observability, versioning, and automated deployment pipelines preferred Strong problem-solving skills with the ability to navigate ambiguity, experiment rapidly, and deliver impactful … cost efficiency while supporting increasing AI adoption and usage Implement engineering best practices around observability, monitoring, testing, security, and operational excellence Establish and champion MLOps practices including model lifecycle management, prompt versioning, automated evaluation, and continuous improvement Build reusable frameworks, developer tooling, and platform capabilities that accelerate AI innovation across ...

Head of Engineering and Technical Architect Cloud & Platform Integration: Partner closely with our GCP and Data Engineering teams to build seamless LLMOps/MLOps CI/CD pipelines, ensuring scalable and cost-effective model deployment via Vertex AI and containerized environments. Take ownership of building and maintaining robust LLMOps pipelines. … data warehouse architectures. Hands-on experience with Google Cloud Platform (GCP) services including Vertex AI, BigQuery, Cloud SQL, and Google Cloud Storage (GCS). MLOps/LLMOps Pipelines: Proven track record of architecting pipelines for model deployment, performance tracking, hyperparameter tuning, and containerized workflows using Docker and Kubernetes (GKE/ ...

full AI engineering lifecycle, from architecture to production deployment, working with multi-disciplinary teams across client projects. The role emphasizes scalable MLOps, low-latency AI, and hands-on development in a client-facing, agile environment within Capco’s Technology Delivery team. #J-18808-Ljbffr ...

infrastructure, and data platforms. The role requires 10+ years of software engineering experience including 3+ years in production AI/ML, strong cloud and MLOps fluency, and a #J-18808-Ljbffr ...

model performance, with strong object-oriented programming, machine learning and statistical skills, and experience taking models into production, designing ML pipelines and working with MLOps, CI/CD and Azure. Key Responsibilities Delivery of data science products Leading data science projects end-to-end, from problem framing through development, deployment … support the business with proactive analytics and insights. Using generative AI to enrich insight and unlock new opportunities, deployed and maintained through the same MLOps patterns applied to traditional models. Engineering and MLOps standards Designing, building and maintaining machine learning pipelines in a cloud environment, applying sound software engineering practice. ...