26 to 50 of 91 Vertex AI Jobs in the UK

Machine Learning Engineer (Conversational AI) Clearance: BPSS Eligible Start: ASAP Work pattern: Hybrid Work type: 12 month FTC (Competitive Salary) Amber Labs are supporting a major government programme focused on transforming public services through the use of AI and automation. This programme is shaping how people interact with digital services across departments — improving accessibility, efficiency, and … user experience. We’re looking for a Machine Learning Engineer (Conversational AI) to help design and build advanced conversational and agentic AI solutions. You’ll work with multi-disciplinary teams to deliver innovative AI-driven tools and services that make a real impact on the public sector. Key Responsibilities: Design and develop conversational AI … accuracy, and cost efficiency. Build evaluation pipelines to ensure model reliability and stability. Develop secure and scalable Python applications and RESTful APIs (FastAPI, Django REST Framework). Integrate AI services and foundation models from providers such as Azure AI , Amazon Bedrock , and Google Vertex AI . Work with vector databases and retrieval More ❯

Machine Learning Engineer (Conversational AI) Clearance: BPSS Eligible Start: ASAP Work pattern: Hybrid Work type: 12 month FTC (Competitive Salary) Amber Labs are supporting a major government programme focused on transforming public services through the use of AI and automation. This programme is shaping how people interact with digital services across departments — improving accessibility, efficiency, and … user experience. We’re looking for a Machine Learning Engineer (Conversational AI) to help design and build advanced conversational and agentic AI solutions. You’ll work with multi-disciplinary teams to deliver innovative AI-driven tools and services that make a real impact on the public sector. Key Responsibilities: Design and develop conversational AI … accuracy, and cost efficiency. Build evaluation pipelines to ensure model reliability and stability. Develop secure and scalable Python applications and RESTful APIs (FastAPI, Django REST Framework). Integrate AI services and foundation models from providers such as Azure AI , Amazon Bedrock , and Google Vertex AI . Work with vector databases and retrieval More ❯

Data & Analytics - Gen AI Engineers x 2 + fully remote contract + initially 6 months + £500 to £530 per day - Inside IR35 Key Skills: + Design of Gen AI Models + RAG + AI/ML Pipelines The Role: + Design, prototype, and deploy Generative AI models (LLMs, Transformers, Diffusion models … document Q&A, report generation, code assistants, etc.). + Apply prompt engineering, RAG (Retrieval-Augmented Generation), and context-aware pipelines to ensure accuracy and relevance. + Integrate AI models with enterprise systems, APIs, and data stores using Python, Java, or Node.js backends. + Collaborate with architects to define scalable and secure AI service architectures. Required … Experience/Skills: Implementing AI/ML pipelines for model training, validation, and deployment (using tools such as MLflow, Vertex AI, or Azure ML). Manage model evaluation, drift monitoring, and continuous improvement processes. Optimize inference performance and cost (e.g., model compression, quantization, API optimization). Ensure compliance with AI ethics, security More ❯

Field Solutions Architect, GenAI, Google Cloud Google London, UK Responsibilities Advise our customers by understanding the customer's business process and objectives. Architect AI driven, spanning Data, AI, and Infrastructure, and work with peers to include the full cloud stack into overall architecture. Work with customers, demonstrate features, tune models, optimize model performance, profiling, and benchmarking. … scripts, templates, reference architectures to enable other customers and internal teams. Work cross-functionally to influence Google Cloud strategy and product direction at the intersection of infrastructure and AI/ML by advocating for enterprise customer requirements. Coordinate regional field enablement with leadership and work with product and partner organizations on external enablement activities. Preferred qualifications Experience with … run benchmarks for existing models, finding opportunities to use accelerators for new models, developing migration paths, and helping to analyze cost to performance. You will work with internal Cloud AI teams to remove roadblocks and shape the future of our offerings. It's an exciting time to join Google Cloud's Go-To-Market team, leading the AI More ❯

Data & Analytics - Gen AI Engineers x 2 + fully remote contract + initially 6 months + £500 to £525 per day - Inside IR35 Key Skills: + Design of Gen AI Models + RAG + AI/ML Pipelines The Role: + Design, prototype, and deploy Generative AI models (LLMs, Transformers, Diffusion models … document Q&A, report generation, code assistants, etc.). + Apply prompt engineering, RAG (Retrieval-Augmented Generation), and context-aware pipelines to ensure accuracy and relevance. + Integrate AI models with enterprise systems, APIs, and data stores using Python, Java, or Node.js backends. + Collaborate with architects to define scalable and secure AI service architectures. Required … Experience/Skills: Implementing AI/ML pipelines for model training, validation, and deployment (using tools such as MLflow, Vertex AI, or Azure ML). Manage model evaluation, drift monitoring, and continuous improvement processes. Optimize inference performance and cost (e.g., model compression, quantization, API optimization). Ensure compliance with AI ethics, security More ❯

we grow, we are always looking for extraordinary talent who want to be part of this our success and help drive our limitless ambitions. About the role The AI & ML Engineering team accelerates the adoption of AI across the business, championing innovation while ensuring our machine learning products are robust, scalable, and cost-efficient. We enable … teams to solve problems using existing AI tools where possible and build custom solutions when needed. Our remit spans AI enablement, agentic systems development, and "conventional" ML engineering for non-GenAI applications like recommender systems. This is a highly visible, hands-on engineering role with a strong focus on pragmatic, production-ready solutions that drive real … role and team collaborate closely with the wider Data team (Data Science, Core Data Engineering) and the wider organisation (Technology, Legal, Information Security) to onboard/develop & scale AI applications. As AI & ML Engineer you will be responsible for The role covers the full AI/ML engineering lifecycle, from discovery to deployment and More ❯

Role: Gen AI Engineer Location: Remote Contract: 06 Months Rate: 450-500 GBP Per Day Inside IR35 MAX The Gen AI Engineer will be a specialized type of artificial intelligence professional, focused on designing, developing & implementing generative AI models and algorithms. Working collaboratively with the team to ensure project deadlines are met. Design, prototype … and deploy Generative AI models (LLMs, Transformers, Diffusion models) for enterprise use cases. Build and fine-tune LLM-based applications (chatbots, summarization, document Q&A, report generation, code assistants, etc.). Apply prompt engineering, RAG (Retrieval-Augmented Generation), and context-aware pipelines to ensure accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data … stores using Python, Java, or Node.js backends. Collaborate with architects to define scalable and secure AI service architectures. Experience in the following Implementing AI/ML pipelines for model training, validation, and deployment (using tools such as MLflow, Vertex AI, or Azure ML). Manage model evaluation, drift monitoring, and continuous improvement More ❯

forecasting). Practical experience with Keras or PyTorch is required. Full-Stack Deployment: Demonstrable experience taking models to production, including building and deploying APIs with FastAPI and using Vertex AI for ML workflows. Visualization & Communication: Ability to create clear visualizations and effectively communicate technical findings to non-technical stakeholders. Highly desirable skills include: Football Analytics Domain … Significant plus if experienced with football datasets (event, tracking, etc.) and visualization libraries like mplsoccer . Advanced MLOps & Modelling: Deeper experience with the Vertex AI lifecycle (especially Pipelines ) and advanced modelling techniques relevant to football (player valuation, tactical analysis). Bayesian Modelling: Experience with probabilistic programming (e.g., PyMC). Stakeholder Management: Proven success working directly with More ❯

methodological improvements to the statistical experimentation engine in a scalable and future-proof manner. What will you bring to the team? Dedication to Data Engineering such as Google Vertex AI pipelines, Airflow/DBT Proficiency in Python for engineering applications Experience with setting up, deploying, and managing cloud infrastructure using Infrastructure as Code (Terraform). Strong … across the product development lifecycle, including automated testing, CI/CD, and code reviews. Comfortable working with various technologies across the software and data engineering stack, including Airflow, Vertex AI, Kubernetes, Docker, GitHub Actions, Jenkins, Google Cloudbuild, Prometheus, and Grafana. Solid experience in cloud data storage , with particular expertise in Google BigQuery (GBQ), GCS/S3 More ❯

Contract AI Engineer (6-Month Initial Engagement | Remote) Location: UK or Poland Engagement: 6-Month Contract | Competitive Day Rate About Us Intelligence Connected partners with leading organisations to deliver high-impact AI, data, and digital transformation projects. We combine deep domain expertise with a network of senior associates and engineers to accelerate outcomes for global clients. … The Role We’re looking for a hands-on AI Engineer to join one of our end-client projects. You’ll help design, build, and deploy production-grade AI and ML solutions that drive measurable business value. What You’ll Do Develop, fine-tune, and deploy ML models (LLMs, NLP, or computer vision depending on project … scope) Work closely with data scientists, engineers, and client stakeholders to translate use cases into scalable technical solutions Build and optimise data pipelines and MLOps workflows Integrate AI components into broader data or product architectures Stay current with emerging AI frameworks, libraries, and model optimisation techniques What We’re Looking For Strong Python and ML ecosystem More ❯

Architect will assess the maturity and effectiveness of data science practices across teams, focusing on how data science is structured, executed, and governed within the organization. Unlike the AI Architect, who evaluates individual AI capability, and the Data & AI Architect, who focuses on technical systems and platform maturity, this role centers on evaluating analytical … for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and … data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch More ❯

Architect will assess the maturity and effectiveness of data science practices across teams, focusing on how data science is structured, executed, and governed within the organization. Unlike the AI Architect, who evaluates individual AI capability, and the Data & AI Architect, who focuses on technical systems and platform maturity, this role centers on evaluating analytical … for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and … data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch More ❯

like LangChain or LlamaIndex. Familiarity with tools for working with Large Language Models via API or in a local context (e.g. HuggingFace transformers). Practical experience using managed AI services and foundation models from a major cloud provider (e.g., Amazon Bedrock, Google Vertex AI, Azure AI Services). Experience with a major … conversational AI platform (Google Dialogflow, Amazon Lex, Rasa, or similar). A solid understanding of core Python ML libraries (Keras, scikit-learn, Pandas) and deep learning frameworks (TensorFlow, PyTorch). Desirable (but not essential) experience: Working with tools/interfaces for AI applications e.g. MCP protocol. Training traditional ML and DL models using tools like Axolotl … LoRA, or QLoRA. Experience with multi-agent orchestration frameworks (LangGraph, AutoGen, CrewAI) Experience with observability and evaluation tools for LLMs such as TruLens or Helicone. Experience with AI safety and reliability frameworks like Guardrails AI. More ❯

like LangChain or LlamaIndex. Familiarity with tools for working with Large Language Models via API or in a local context (e.g. HuggingFace transformers). Practical experience using managed AI services and foundation models from a major cloud provider (e.g., Amazon Bedrock, Google Vertex AI, Azure AI Services). Experience with a major … conversational AI platform (Google Dialogflow, Amazon Lex, Rasa, or similar). A solid understanding of core Python ML libraries (Keras, scikit-learn, Pandas) and deep learning frameworks (TensorFlow, PyTorch). Desirable (but not essential) experience: Working with tools/interfaces for AI applications e.g. MCP protocol. Training traditional ML and DL models using tools like Axolotl … LoRA, or QLoRA. Experience with multi-agent orchestration frameworks (LangGraph, AutoGen, CrewAI) Experience with observability and evaluation tools for LLMs such as TruLens or Helicone. Experience with AI safety and reliability frameworks like Guardrails AI. More ❯

I'm hiring for an AI project focused on Agentic AI systems deployed on Google Cloud Platform (GCP). This is a opportunity to work with a forward-thinking consultancy delivering real-world AI solutions to public and private sector clients.Details- Proven experience building Agentic AI systems (e.g. autonomous agents, multi-agent … orchestration, tool use, memory, planning) Strong hands-on skills in Python, LLMs, RAG, and LangChain or similar frameworks Deep understanding of GCP services: Vertex AI, BigQuery, Cloud Functions, Pub/Sub, etc. Experience with batch and real-time data pipelines Familiarity with AI assurance, governance, or ethical AI is a bonus Ability More ❯

I'm hiring for an AI project focused on Agentic AI systems deployed on Google Cloud Platform (GCP). This is a opportunity to work with a forward-thinking consultancy delivering real-world AI solutions to public and private sector clients. Details- Proven experience building Agentic AI systems (e.g. autonomous agents, multi … agent orchestration, tool use, memory, planning) Strong hands-on skills in Python, LLMs, RAG, and LangChain or similar frameworks Deep understanding of GCP services: Vertex AI, BigQuery, Cloud Functions, Pub/Sub, etc. Experience with batch and real-time data pipelines Familiarity with AI assurance, governance, or ethical AI is a bonus More ❯

call TCS London Office number 02031552100/+44 204 520 2575 with the subject line: “Application Support Request”. Do you have the expertise in developing and implementing AI solutions? We have a great role for you – AI Engineer! Careers at TCS: It means more TCS is a purpose-led transformation company, built on belief. We … the range of teams within the business to bring products to life. Opportunity to work for one or more large UK & European Banking clients. The Role: As an AI Engineer , you will join our dynamic technology and compliance team, focusing on regulatory adherence and automation of controls within the banking sector. You will be responsible for designing, developing … and deploying AI-powered systems, specifically leveraging Large Language Models (LLMs) on Google Cloud, to detect, interpret, and respond to changes in regulatory policies, ensuring that the controls remain current and effective. Key Responsibilities: Develop and implement AI solutions using LLMs to monitor, parse, and summarise regulatory policy changes from multiple jurisdictions and sources. Automate the More ❯

call TCS London Office number 02031552100/+44 204 520 2575 with the subject line: “Application Support Request”. Do you have the expertise in developing and implementing AI solutions? We have a great role for you – AI Engineer! Careers at TCS: It means more TCS is a purpose-led transformation company, built on belief. We … the range of teams within the business to bring products to life. Opportunity to work for one or more large UK & European Banking clients. The Role: As an AI Engineer , you will join our dynamic technology and compliance team, focusing on regulatory adherence and automation of controls within the banking sector. You will be responsible for designing, developing … and deploying AI-powered systems, specifically leveraging Large Language Models (LLMs) on Google Cloud, to detect, interpret, and respond to changes in regulatory policies, ensuring that the controls remain current and effective. Key Responsibilities: Develop and implement AI solutions using LLMs to monitor, parse, and summarise regulatory policy changes from multiple jurisdictions and sources. Automate the More ❯

Role: Lead Data Scientist Location: London (3 days per week onsite) Salary: £98,000 + Bonus Start Date: ASAP A leading AI-driven insights and analytics business is seeking a Lead Data Scientist to play a pivotal role in shaping the organisation’s data strategy. You’ll lead complex data science projects from inception to deployment while mentoring … of analysts and data scientists. This company combines qualitative research with quantitative data science to uncover the attitudes and behaviours driving customer decisions. The team leverages technology and AI to enhance, not replace, human creativity and insight. Responsibilities - Lead end-to-end execution of complex data science projects integrating statistical modelling, machine learning (ML), and deep learning (DL … architectures. - Establish modelling frameworks with statistical quality control, detecting drift and decay. - Drive best practices for model explainability (e.g., SHAP/LIME) and scalable ML systems (including generative AI, NLP, CV, and recommendation engines). - Partner with engineering teams to ensure robust deployment and adherence to MLOps principles. - Shape and consult on broader data strategy and infrastructure. - Mentor More ❯

Role: Lead Data Scientist Location: London (3 days per week onsite) Salary: £98,000 + Bonus Start Date: ASAP A leading AI-driven insights and analytics business is seeking a Lead Data Scientist to play a pivotal role in shaping the organisation’s data strategy. You’ll lead complex data science projects from inception to deployment while mentoring … of analysts and data scientists. This company combines qualitative research with quantitative data science to uncover the attitudes and behaviours driving customer decisions. The team leverages technology and AI to enhance, not replace, human creativity and insight. Responsibilities - Lead end-to-end execution of complex data science projects integrating statistical modelling, machine learning (ML), and deep learning (DL … architectures. - Establish modelling frameworks with statistical quality control, detecting drift and decay. - Drive best practices for model explainability (e.g., SHAP/LIME) and scalable ML systems (including generative AI, NLP, CV, and recommendation engines). - Partner with engineering teams to ensure robust deployment and adherence to MLOps principles. - Shape and consult on broader data strategy and infrastructure. - Mentor More ❯

leadership, data engineering, infrastructure and DevOps, data/metadata/knowledge platforms, and GenAI/ML, compute, and analysis platforms. We're seeking a highly skilled Director for AI/ML, Compute, Infra & DevOps Platforms products. In this role you will develop the product strategy for our core developer platforms, combine technical depth with strategic vision, and lead … teams to drive product success in a cutting edge R&D setting. Key Responsibilities Develop and execute a comprehensive product strategy for our platform products, including AI/ML, GenAI, Compute/Analytics, Cloud/Physical Infrastructure, and DevOps platforms. Define and prioritize features, enhancements, and functionalities based on user analysis, customer feedback, and business requirements. Plan and … services. Hands on experience with DevOps and engineering tools (GitLab, GitHub, Azure DevOps, Docker, Kubernetes). Proficiency with AI/ML and MLOps platforms (Databricks, Google Cloud Vertex AI, SageMaker). Familiarity with generative AI technologies and frameworks (OpenAI, Google Gemini, Hugging Face Transformers). Demonstrated success in developing and executing product More ❯

About the Company Our client is an emerging health technology company using AI to modernise digital care and pharmacy infrastructure. Our platform connects clinical operations with intelligent, patient-focused experiences - removing friction, improving coordination, and enabling more personalised care at scale. Building a collaborative, mission-driven team that values creativity, ownership, and innovation. You’ll join at a … formative stage, helping define both our AI systems and the engineering culture that powers them. The Opportunity As a Senior AI Engineer , you’ll lead the design and delivery of production-grade AI solutions that drive real business value. This is a hands-on, end-to-end role - from architecture and model development to … deployment and optimisation. You’ll work closely with product, engineering, and operations teams (and occasionally with enterprise clients) to identify opportunities, translate needs into scalable AI solutions, and bring models into production. What You’ll Do Design and deploy AI systems across areas like personalisation, forecasting, and information retrieval Build and maintain robust data pipelines, model More ❯

About the Company Our client is an emerging health technology company using AI to modernise digital care and pharmacy infrastructure. Our platform connects clinical operations with intelligent, patient-focused experiences - removing friction, improving coordination, and enabling more personalised care at scale. Building a collaborative, mission-driven team that values creativity, ownership, and innovation. You’ll join at a … formative stage, helping define both our AI systems and the engineering culture that powers them. The Opportunity As a Senior AI Engineer , you’ll lead the design and delivery of production-grade AI solutions that drive real business value. This is a hands-on, end-to-end role - from architecture and model development to … deployment and optimisation. You’ll work closely with product, engineering, and operations teams (and occasionally with enterprise clients) to identify opportunities, translate needs into scalable AI solutions, and bring models into production. What You’ll Do Design and deploy AI systems across areas like personalisation, forecasting, and information retrieval Build and maintain robust data pipelines, model More ❯

We are looking for a Machine Learning Engineer Location: London Reporting to: Head of AI The role We are looking for a talented Machine Learning Engineer who thrives in environments where reliability, scale, and impact truly matter. At Rightmove, you'll join a close-knit, collaborative AI team that's developing, shipping and operating live ML …/AI services that help Rightmove deliver exceptional experiences and value to consumers, our partners and all our stakeholders across the UK property market. You'll be at the heart of a greenfield opportunity - building, deploying, and operating machine learning systems that leverage Rightmove's data at large scale. You'll have the opportunity to shape best practices … discipline, and help us move from first launches to robust, sustainable production. In this role, you will work in a cross-functional team to productionise machine learning and AI models, ensuring they are robust, scalable, and measurable. You'll collaborate closely with data scientists, engineers, and product teams to automate workflows, monitor performance, and retrain models as needed. More ❯

+ Car Allowance + 18% Bonus + Equity Are you an accomplished product leader ready to define how world-class compute, infrastructure, and DevOps platforms power AI and scientific discovery at global scale? We’re partnering with a pioneering research-driven organisation investing heavily in AI, ML, and next-generation cloud infrastructure , now seeking a Director … a portfolio that underpins one of the world’s most advanced digital R&D ecosystems. 💡 Why this role? Lead the product strategy and roadmap for platform services enabling AI, ML, and data-driven science. Build and mentor a team of high-performing Product Managers , setting standards for excellence and delivery. Collaborate with engineering, data science, and research leaders … be doing: Defining and executing the platform product roadmap across compute, DevOps, and cloud infrastructure. Partnering with engineering leadership to deliver scalable platform products that enable scientific and AI workloads. Establishing clear goals, metrics, and success criteria for adoption, performance, and business impact. Acting as the senior stakeholder interface, communicating technical strategies to executive and business audiences. Driving More ❯