11 of 11 Remote/Hybrid MLOps Jobs in the City of London

data quality. Stay current with emerging AI and machine learning technologies and identify opportunities for innovation. Your Profile Essential Skills & Experience Proven experience in MLOps, data engineering, software engineering, or machine learning development with recent exposure to Generative AI and advanced analytics. Strong understanding of software engineering best practices, including ...

solutions on GCP leveraging Vertex AI, BigQuery, Cloud Run, secure API integrations; build scalable, resilient, compliant architectures; integrate AI services into existing applications. Data, MLOps & Engineering: Work with Data Engineers and Analysts to prepare, embed, and manage data (vector databases, embeddings); implement CI/CD, monitoring, logging, model performance tracking ...

software development concepts like CI/CD, Version Control, Containers (Docker & Kubernetes) and proven track record of deploying ML models to production and established MLOps concepts. A good command of analytical programming and visualisation languages and libraries (SQL, python, matplotlib, etc.) as well as some of the supporting tools ...

have strong experience across: Generative AI Agentic AI Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Prompt Engineering Machine Learning Intelligent Automation MLOps and LLMOps You'll also have experience working with technologies such as OpenAI, Azure OpenAI, Hugging Face, Llama or similar Large Language Models, alongside vector databases including ...

associated architecture patterns Experience designing and managing APIs including REST and GraphQL Strong understanding of microservices and serverless architectures Practical experience with DevOps and MLOps practices including CI/CD pipelines Knowledge of security frameworks, identity management and authentication standards Desirable Skills for the AI Solutions Architect: Experience with enterprise ...

Mathematics Computer Science or a related quantitative discipline Desirable Skills for the Data Scientist: Experience with deep learning frameworks advanced modelling techniques Familiarity with MLOps concepts model monitoring deployment pipelines Exposure to tools such as Databricks MLflow feature stores Experience working in Agile product-led delivery environments Understanding of data ...

hybrid in London, moving AI from prototype to production across cloud-native platforms. Responsibilities include AI solution design, cloud engineering on GCP, data, MLOps, Responsible AI governance, and collaboration with underwriters and operations. Strong Python and LLM experience required. #J-18808-Ljbffr ...

ensure solutions are secure, ethical, and fit for purpose. Working across multidisciplinary teams, you'll drive innovation in areas like DevOps, platform engineering, and MLOps - balancing experimentation with governance and risk. What you'll be doing: Leading architecture, design, and delivery of digital & AI solutions Driving innovation across AI, analytics ...

experiences, and helping define the next generation customer data and marketing technology ecosystem. Equally important will be establishing how Data Science, AI Engineering and MLOps functions operate together in an AI-enabled business, whilst defining the long-term operating model for Consumer Data Science as the organisation continues its transformation. ...

solutions from development through to deployment and monitoring * Building scalable Generative AI and Agentic AI solutions, including RAG pipelines and orchestration frameworks * Implementing MLOps frameworks, governance and best practices * Translating business requirements into cloud-native AI and data architectures across Azure, AWS and GCP * Collaborating with technical and non-technical … stakeholders to deliver measurable business value * Supporting innovation initiatives, reusable assets, thought leadership and client proposals Candidates should have strong experience in AI Engineering, MLOps and cloud-native AI platforms, alongside hands-on knowledge of technologies such as LangChain, LlamaIndex, MLflow, Kubernetes, Docker and CI/CD tooling. Applicants will ...

Intelligence Architect: Proven experience architecting solutions across Generative AI, Agentic AI, machine learning and automation Strong understanding of prompt engineering, RAG pipelines, model tuning, MLOps and LLMOps Experience delivering enterprise‐scale RAG solutions using LLMs and vector databases Ability to design AI platforms that integrate with existing enterprise technology stacks … services Solid software engineering foundation for building scalable, maintainable AI systems Advanced Python expertise with AI and ML frameworks Experience with MLOps and LLMOps tooling including containerisation and orchestration platforms Proven experience delivering applications using state‐of‐the‐art LLMs including prompt design, fine‐tuning and evaluation Strong understanding ...