1 to 25 of 260 Google Jobs in London

field. Tech Stack LLMs: GPT-4/5, Claude, Gemini, Mistral, LLaMA, Cohere Frameworks: LangChain, LlamaIndex, Haystack Tools: GitHub Copilot, Cursor, PromptLayer, Weights & Biases Cloud: Azure ML, AWS SageMaker, Google Vertex AI, Databricks Infra: Python, Docker, Kubernetes, SQL, PyTorch More ❯

for clients or stakeholders. It would be great but not essential if you had experience of working in an agile team worked with Amazon Web Services, Microsoft Azure, or Google Cloud Platform a working knowledge of Git and version control principles knowledge of popular deep learning frameworks - Hugging Face Transformers library, for example. experience of building LLM applications experience of More ❯

Mistral Large, LLaMA 3, Cohere Command R+, DeepSeek Frameworks: LangChain, LlamaIndex, Haystack, AutoGen, CrewAI Tools: GitHub Copilot, Cursor, LangSmith, LangFuse, Weights & Biases, MLflow, Humanloop Cloud: Azure ML, AWS SageMaker, Google Vertex AI, Databricks, Modal Infra: Python, Docker, Kubernetes, SQL/NoSQL, PyTorch, FastAPI, Redis More ❯

Strong understanding of NLP techniques, including tokenization, embeddings, transformers, and attention mechanisms. Experience in retraining and fine-tuning LLMs using large-scale datasets. Familiarity with cloud platforms like AWS, Google Cloud, or Azure for model training and deployment. Data Skills: Expertise in data preprocessing, augmentation, and management of large datasets for training purposes. Problem-Solving: Strong analytical and problem-solving More ❯

Snowflake, Databricks). · Hands-on experience with data modelling tools, data warehousing, ETL processes, and data integration techniques. · Experience with at least one cloud data platform (e.g. AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark). · Strong knowledge of data workflow solutions like Azure Data Factory, Apache NiFi, Apache Airflow etc · Good knowledge of stream and batch More ❯

Generative AI techniques for text, code, image, and multi-modal use cases using advanced prompt engineering. Utilize modern GenAI toolkits and libraries, including: PyTorch LangChain, LangGraph, Model Context Protocol, Google's Agent Development Kit (ADK), and similar agentic frameworks. Develop experiments for LLM fine-tuning, retrieval-augmented generation (RAG), and multi-agent AI workflows . Deliver production-grade Python code More ❯

analysis and margin optimisation . Tech Environment Core Skills: SQL (essential), Power BI (advantageous) Platform: Microsoft Fabric (mid-implementation) Languages: Python (pandas/numpy - desirable, not essential) Other: Salesforce & Google Analytics exposure beneficial About You Proven experience as an Insight Analyst , ideally in wholesale, distribution, or another product-heavy industry. Strong knowledge of pricing, rebates, and margin analysis . Excellent More ❯

d love to hear from you. Apply today to learn more about this opportunity. Desired Skills and Experience Python, Node, Node.js, AWS, Amazon Web Services, Azure, Microsoft Azure, GCP, Google Cloud Platform, VP, VP of Engineering, CTO More ❯

helping the organisation become truly data-driven. What you’ll do as the Data Analyst: Develop and maintain Power BI dashboards and reports from multiple sources (SQL Server, Excel, Google Analytics, finance & grant systems). Write and optimise SQL queries to ensure accuracy and integrity of data. Champion best practice in data governance, security, and reporting processes. Present insights and More ❯

framework Data BigQuery - Cloud data warehouse Dataform - SQL transformation framework - Semantic layer/analytics API Superset - Presentation layer Algolia/Vertex AI Search - Search PostgreSQL - App data Infrastructure & DevOps Google Cloud Platform (GCP) - Cloud provider Pulumi - Infrastructure as Code (TypeScript) GitHub Actions - CI/CD Firebase - Feature flags Cloudflare - CDN and DNS AI & Machine Learning Python BAML - LLM prompt engineering More ❯

have PhD in a relevant field. Familiarity with agronomy concepts and agricultural systems. Expertise in deep learning techniques. Experience with cloud-based geospatial processing and big data technologies (e.g., Google Earth Engine, Spark). Additional Information Location: Remote working is possible within UK. Portfolio submission: Please provide examples of relevant geospatial data science projects. What we offer? Extensive benefits package More ❯

exhibition). Experience with partner co-op marketing. Familiarity with design tools (Canva, Adobe InDesign) and video editing tools (Adobe Premiere Pro). Knowledge of analytics platforms such as Google Analytics, Semrush, or similar tools. PERSONAL QUALITIES Excellent organizational, communication, and interpersonal skills. Self-starter with the confidence to manage campaigns independently. Collaborative mindset with the ability to build strong More ❯

teams, make life at Savanta feel more like working at a 'boutique' agency. Our client portfolio includes some of the world's most recognizable and valuable brands such as Google, UBS, Meta, Pandora, Vodafone, Samsung, Heineken, LEGO, Aston Martin, ING, Unilever, and the Cabinet Office. Savanta is committed to being an equal opportunities employer and continuously strives to be an More ❯

time-dependant data. Deep learning and neural networks. LLM Operations Expertise in managing and operationalising large language models. Experience in deploying models on cloud platforms (e.g. AWS, Sage maker, Google AI Platform, IBM Watson) IND_PC3 Guidant, Carbon60, Lorien & SRG - The Impellam Group Portfolio are acting as an Employment Business in relation to this vacancy. More ❯

personal engineering standards. You lead by example rather than authority. Nice to have Experience with Redis and Celery. Experience scaling multi-tenant SaaS applications. Experience with cloud platforms. (AWS, Google Cloud or Azure). Knowledge of containerisation (Docker or Kubernetes) Familiarity with SOC 2 readiness and security best practices. Experience with observability and monitoring. Background in fintech, lending or other More ❯

skills in Python Experience with AWS or GCP Demonstrated experience and responsibility with data, processes, and building ETL pipelines. Experience with cloud data warehouses such as Amazon Redshift, and Google BigQuery. Building visualizations using tools such as Looker studio or equivalent Experience in designing ETL/ELT solutions, preferably using tools like Airflow or AWS Glue Solid analytical and technical More ❯

Core skills, knowledge and experience required Audio and video processing - Understanding of audio and video processing principles Virtualisation & Cloud Computing – proficiency with virtualisation and cloud computing eg AWS, Azure, Google Cloud platforms. Multiplexing - Proficiency in encoding and multiplexing technologies Diagnostic tools - Proficiency in diagnostic engineering tools and software Analytical and technical problem-solving skills to diagnose and resolve technical issues More ❯

Experience with TypeScript. Familiarity with GraphQL or other modern data-fetching technologies. Experience in integrating message brokers (e.g., RabbitMQ, Kafka). Familiarity with cloud platforms like AWS, Azure, or Google Cloud. Knowledge of microservices architecture and related tools. Experience with testing frameworks like Mocha, Chai, or Jest. Familiarity with front-end technologies like React, Vue, or Angular is a plus. More ❯

Mesh, Data Fabric, Data Lake etc. Data/Analytics - solving enterprise data and analytics problems using technology Cloud - hands-on Public Cloud experience in either AWS/Azure/Google, both their 'services' and 'how' to work in the cloud such as DevOps-centric approach Security - having worked in sensitive data environments and ideally have experience facing off to cyber More ❯

focus on either structured data (like CRM records and support tickets), or unstructured data (like documents and emails). Computer AirSync connects everything, unifying all your data sources (like Google Workspace, Jira, Notion) into one AI-ready source of truth: Computer Memory. Powerful search, reasoning, and action Once connected to all your tools and apps, Computer is embedded in your More ❯

Languages: C#, Python, SǪL Tech Stack: Azure GCP, DDD, EDA, Microservices, API Integration, Distributed Systems Architecture Frameworks: TOGAF, Well Architected, CNCF Cloud Platforms: Microsoft Azure, K8s, familiarity with AWS, Google Cloud Platform Must Have : TOGAF certification, Cloud experience (Azure), Terraform, CI/CD (ADO/GHA), API design and integration Technologies: EDA, Microservices, API Integration, DDD, Distributed Systems Tools: Visio More ❯

and identify automation opportunities. Skills & Experience: Proven experience developing digital or media-focused technology solutions. Strong programming skills (JavaScript, TypeScript, Python, or similar). Experience with cloud platforms (preferably Google Cloud Platform) and serverless architecture. Advanced SQL and data warehousing skills (e.g. BigQuery). Familiarity with front-end frameworks such as React. Experience with ETL/ELT processes and data More ❯

ceremonies and code reviews to uphold quality and delivery standards. Tech Stack & Skills Core skills: Strong Python backend development experience (FastAPI or similar frameworks) Cloud-native deployment experience (preferably Google Cloud and Cloud Run) Unit testing experience (pytest or similar frameworks) Familiarity with agile development and CI/CD processes Strong understanding of Git/GitHub workflows and DevOps tooling More ❯

A self-starter with an analytical mindset and ability to work autonomously. Experience with Digital/Social Media Data and APIs. Knowledge of Salesforce Sales/Marketing Cloud or Google Analytics. Background in BI tool migration/implementation. What you'll get in return Enjoy hybrid working (one day a week in the office) 25 days holiday (+ bank holidays More ❯

ways. Role Overview As a Full Stack Commerce Engineer Manager , you will: Lead client-facing engagements and design AI-powered solutions. Build full-stack applications integrating Generative AI (OpenAI, Google Gemini, Nvidia). Architect data flows across enterprise platforms (DAM, PXM, CDP, CMS, CRMs). Work with cloud platforms (Azure/GCP) and advanced databases (SQL/NoSQL). Mentor More ❯