401 to 425 of 635 MLOps Jobs in the UK

programs; Collaborate with data engineers, clinicians, and business teams to tailor solutions to client needs; Deploy AI and machine learning models in production using MLOps and LLMOps practices; Use cloud platforms and data solutions to ensure scalability and operational integrity; Present data-driven recommendations to senior audiences and demonstrate … real‐world datasets; Familiarity with NLP and deep learning techniques applied to biomedical data; Knowledge of Azure, AWS, or GCP and model deployment using MLOps frameworks; Strong Python and SQL programming skills, with experience in PyTorch, TensorFlow, and Hugging Face; Experience with Databricks, Spark, and other data platforms ...

environments and bare-metal local hardware. API Development: Create high-performance, asynchronous REST and WebSocket APIs using FastAPI to serve real-time conversational agents. MLOps & Infrastructure CI/CD Automation: Design automated machine learning pipelines for model testing, versioning, and continuous deployment. Containerization: Pack applications using Docker or Podman … SageMaker), Azure (Azure ML), and GCP (Vertex AI). CI/CD Tools: Experience with GitLab CI, GitHub Actions, Jenkins, or specialized MLOps platforms (e.g., Kubeflow, MLflow). Preferred Qualifications Conversational Context: Experience with dialogue management, prompt engineering, and Retrieval-Augmented Generation (RAG). Data Analytics: Familiarity with real-time ...

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/ ...

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 Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery … 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 Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration ...

Data Science, who owns AI/ML and data governance direction at ComplyAdvantage. Your remit is execution: the architectural design of our company-wide MLOps and agentic AI platforms, the build-out of new models and agent systems, and the engineering bar across all of it. You will also represent … financial crime a thing of the past. Scope of the roleScope & Key ResponsabilitiesArchitectural Leadership: Lead the architectural design and implementation of our company-wide MLOps and agentic AI platforms, covering training, evaluation, serving, feature/vector stores, and agent orchestration. Strategic Execution: Translate the ML and agentic AI roadmaps ...

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 ...

systems tailored to audit applications. Contribute to architectural decisions and solution governance. Write clean, efficient, and scalable code that adheres to software engineering principles, MLOps practices, and cloud-native development. AI Solution Delivery: Own the implementation of ML pipelines, APIs, and data integration workflows. Operational Excellence: Contribute to defining reusable … development patterns, enforcing coding standards, and implementing MLOps best practices that support version control, performance optimisation, and maintainability. Cross-Disciplinary Collaboration: Work side-by-side with data scientists, product managers, platform engineers, and QA teams to align on technical requirements, delivery timelines, and integration plans. Provide hands-on contributions ...

domains like customer service, document automation, summarization, and knowledge retrieval. Fine-tune or adapt foundation models using domain-specific data. Collaborate with data engineers, MLOps, and product teams to build end-to-end AI applications and APIs. Develop custom prompts and prompt chains using tools like LangChain, LlamaIndex, PromptFlow … workflows and deploy them via APIs or web apps (e.g., FastAPI, Streamlit, Flask). Familiarity with cloud platforms (AWS/GCP/Azure) and MLOps best practices. Excellent communication skills with the ability to translate technical solutions into business impact. Skills and Personal attributes we would like to have: Experience ...

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 ...

part of the Data and AI platform team; you’ll get to pioneer on real world problems, bringing your knowledge of AI/ML, MLOps and LLMs to bear - collaborating cross team to make your vision a reality. You’ll be backed by our platform team, and have a wealth … scientific evaluation with the operational maturity to champion high-value applications and confidently push back on unsuitable AI use cases. Design, refine and build MLOps component of the data and AI platform, from Vector Databases through feature stored and model serving, all at the millisecond scale. Implement CI/ ...

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/ ...

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/ ...

## AI EngineerApplylocations: Kings Cross, Londontime type: Full timeposted on: Posted 11 Days Agojob requisition id: UMG-25167Music is Universal It’s the passionate and dedicated team at Universal Music who help make us the ...

teams own the full delivery lifecycle, from early ideas through to production systems that create measurable impact for our customers and the business. As MLOps Engineering Manager, you will help shape how we build, deploy and operate machine learning products at scale, working closely with ML Engineers, Data Engineers, Software … Engineers, Data Scientists, Product Managers and stakeholders across Trainline. Responsibilities Build and lead a new team of MLOps Engineers, creating an environment where people can do their best work while delivering meaningful outcomes for customers and the business. Define and evolve MLOps processes, tooling and infrastructure choices across the technology ...

Databricks seeks a senior technologist to architect production-grade ML and AI workloads, spanning end-to-end pipelines, training/inference optimization, and MLOps lifecycle management with cloud-native integration. You will lead GenAI initiatives, advise solution architects during pre-sales and post-sales cycles, influence the AI roadmap ...

guide enterprise customers in building production-grade ML and AI applications on the Databricks Data Intelligence Platform. You will mentor colleagues and advance GenAI, MLOps, and LLMOps expertise while shaping the platform roadmaps. You will partner with field engineers and Solution Architects to deliver end-to-end AI solutions, strong ...

Senior ML/MLOps Engineer A career at Booksy means you're part of a global team focused on helping people around the world feel great about themselves, every day. From empowering entrepreneurs to build successful businesses, to supporting customers in arranging their 'me time' moments … path to production, and build something that stays healthy at real scale — you'll feel right at home. As a Senior ML/MLOps Engineer, you'll be a foundational hire in our new Data Science & Applied AI function — working in close partnership with our Data Scientists to take intelligent ...

colleagues. You will work with solution architects, lead GenAI initiatives, and influence the AI roadmap while maintaining cutting-edge expertise in areas like GenAI, MLOps, and LLMOps. #J-18808-Ljbffr ...

evolve the backend platform supporting their AI services, ensuring reliable operations for local authority clients. The ideal candidate has strong Python skills, experience in MLOps, and a solid background in Azure-native technologies. This hybrid role is based in London, requiring office attendance at least 1-2 days a week. ...

services, while guiding the technical direction for enterprise-scale backend services. You will build scalable backend services, data pipelines, and platform components, champion MLOps #J-18808-Ljbffr ...

deploy scalable, responsible AI solutions for UK public sector clients, including Defence, Government and Security. You will deliver production-ready models and contribute to MLOps capabilities while working across multidisciplinary teams. This hands-on role involves Generative AI, NLP, data pipelines and API services, with opportunities to shape proposals ...

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. ...

CODAS project and related initiatives at AND-E Lab. Ideal candidates have 5+ years in ML/AI, strong Python, cloud/MLOps experience, and a collaborative mindset to work with partners and stakeholders across experiments and #J-18808-Ljbffr ...