451 to 475 of 2,164 GCP Jobs

core Big Data Analytics domain with some exposure to advanced proofs‐of‐concept and an understanding of a major public cloud platform (AWS, GCP, Azure). Experience diving deeper into solution architecture and design. The role requires travel to customer sites in the UK. Travelling approx. ...

with the ability to manage multiple concurrent vacancies in a fast-paced environment. Experience supporting global technology organisations. Knowledge of cloud technologies (AWS, Azure, GCP), DevOps, cybersecurity, data platforms, and emerging AI technologies. Experience hiring for AI, Machine Learning, Generative AI, and cloud-native technology roles. Why Apply? Opportunity ...

fast‐moving environments where requirements evolve quickly. A bias toward ownership, pragmatism, and delivering useful solutions. Nice to Have Experience with cloud platforms (AWS, GCP, Azure) and infrastructure telemetry. Familiarity with distributed systems, monitoring data, or usage-based billing data. Experience supporting customer-facing data products or platforms. What ...

based environments. Knowledge of UK Government security and compliance frameworks, including: JSP 604 Secure by Design Experience across multiple cloud platforms including: AWS Azure GCP What Success Looks Like Viewing obstacles as opportunities for growth. Taking ownership and maintaining a strong bias towards action. Providing constructive, compassionate and direct feedback. ...

clustering, and correlation algorithms. Generative AI: Experience with LLM prompting, Retrieval-Augmented Generation (RAG), and LangChain. Cloud Infrastructure: Deep understanding of AWS, Azure, or GCP infrastructure components Additional Preferred Qualifications: Experience with enterprise observability and AIOps platforms such as ServiceNow ITOM, Splunk, Dynatrace, Datadog, BigPanda, New Relic, or similar platforms. ...

industry DS/ML experience, with a focus on either: ML Engineering: Building/maintaining production‐grade cloud infrastructure (AWS/Azure/GCP) that supports deployment of ML applications and monitoring ML model performance. Data Science/AI: Applying advanced techniques in LLMs, agentic systems, vector databases, fine‐tuning ...

Infrastructure fundamentals (e.g., Datacenter, Networks, Compute, Storage) Cloud and Infrastructure Migrations, Operations and Lifecycle management Cloud services (e.g., Amazon Web Services, Microsoft Azure, Google Cloud Platform) Cloud and Infrastructure Security & Resilience (DR, HA, Backup & Recovery) Virtualization Platforms (e.g., VMware, Hyper-V, Nutanix) Container Platforms (e.g., Openshift, EKS, AKS, GKS) Infrastructure ...

solutions Experience using enterprise architecture tools such as LeanIX, Avolution, Orbus, Bizzdesign or similar Relevant certifications (e.g. TOGAF, COBIT, DCAM, AWS/Azure/GCP architecture ) Knowledge of DAMA-DMBOK Security requirements (mandatory) Please note that any offer and commencement of employment is subject to : Confirmation that you already hold ...

industry DS/ML experience, with a focus on either: ML Engineering: Building/maintaining production-grade cloud infrastructure (AWS/Azure/GCP) that supports deployment of ML applications and monitoring ML model performance. Data Science/AI: Applying advanced techniques in LLMs, agentic systems, vector databases, fine-tuning ...

MLOps, and cloud-native architectures Track record of leading ML/AI technical initiatives across multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails ...

define metrics, generate actionable insights, and drive decisions based on operational data. Hands-on experience with cloud platforms such as Amazon Web Services, Google Cloud Platform, or Microsoft Azure, and infrastructure-as-code tooling including Terraform. Systematic problem-solving and troubleshooting skills applied to complex, distributed systems in production environments. ...

Exchange Online, Outlook, Office, OneDrive, SharePoint Online, Microsoft Power Platform, Azure, Scripting, Active Directory, Archiving Services). Strong experience managing cloud environments (Azure, AWS, GCP), including security groups, resource groups, load balancers, storage, backup & recovery, and networking. Experience configuring Azure resources such as Virtual WAN, Application Gateway, Route Tables ...

asset management, wealth management, or client-facing financial technology platforms Familiarity with cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform Exposure to event-driven architecture and distributed systems design Experience with modern front-end component libraries and design systems ABOUT US J.P. Morgan ...

Good understanding of MLOps stack (CI/CD, monitoring, pipelines) Familiarity with tools like MLflow, Airflow, Evidently, DVC, Docker, Kubernetes. Cloud experience (AWS/GCP/Azure) Some mentoring/leadership experience + desire to grow into management Nice to have: Experience scaling ML platforms or teams Fintech/lending ...

lakes — with an advanced level of SQL. Strong logical/conceptual data modelling and solution design skills. Experience with cloud platforms (AWS, Azure, or GCP). Exposure/experience in XML and SOAP/REST/JSON. Bonus knowledge Experience in regulated industries such as Financial Services, Insurance, or Life ...

hands‐on technical work, ensuring seamless translation of vision into actionable outcomes. Familiar with hyperscaler AI/ML services (Azure OpenAI, AWS Bedrock, GCP Vertex AI), capable of architecting and delivering cloud‐native solutions, driving joint co‐sell motions with hyperscaler partners, and accelerating adoption through marketplace offerings. Operationalizes ...

industry. Your Technical Expertise: Architectural and/or feature knowledge of one or more of the listed Data and AI Platforms: Google Cloud Platform, Amazon Web Services, Microsoft Azure, and Databricks. Experience in one or more of the listed Languages such as: Python, R, PySpark Experience in one or more ...

modern software development practices and tools (e.g. Agile, version control, automated testing, CI/CD, observability) Understanding of cloud platforms (e. g., AWS, Azure, GCP) and containerization technologies (e. g., Docker, Kubernetes) Please note that we do not offer sponsorship for our London office. Flow Traders does not accept unsolicited ...

right task, you can expect to work with the following technologies to ensure scalable, high-performance applications: Cloud \& Platforms: AWS, Azure, Google Cloud Platform, IBM, Oracle, Salesforce Architecture \& Delivery: Microservices, packaged solutions, cloud/on-premise models, agile delivery, digital transformation Tools \& Frameworks: IoT, cloud-native architectures, UML, ArchiMate *Please ...

Apple's technology stack Experience building and operating enterprise‐grade ML pipelines (data preparation, distributed training, model optimisation, serving, and monitoring) in cloud (AWS, GCP, Azure) or on‐prem environments Preferred Qualifications Demonstrated ability to deliver end‐to‐end AI products - from problem framing and experimentation through to globally deployed ...

solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts ...

solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts ...

solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts ...

solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts ...

similar) and an eye for interfaces that feel considered rather than merely functional. Cloud infrastructure. Experience deploying and operating distributed services on AWS, GCP, or Azure. Containers and orchestration. Docker and Kubernetes in production. Real-time data. Experience processing or analysing real-time data streams at scale. Retail or personalisation. ...