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Designs and operates scalable AI/ML platforms, automates DevOps pipelines, and manages cloud/Kubernetes infrastructure for production workloads.
Base Pay Range Direct message the job poster from Innova Recruitment Co-Founder & Director | 15+ Years in Tech Recruitment | Building High-Performing Engineering, Data & IT Teams Across the UK & USA Private…
Data Engineer Gigged AI is an On demand talent marketplace specialising in the IT and technology sector. We have an opportunity live at the moment for a Data Engineer - Outside IR35 his is a Hybrid role in Scotland,…
What we do. Electric Car Leasing Why we do it. Greener. Fairer. Future. At Octopus Electric Vehicles we've built a data platform that provides data services to all areas of our business. The aim of the platform is…
JOB TITLE: Lead Data Engineer SALARY: £92,701 - £109,060 LOCATION: Edinburgh, Leeds, Manchester, Bristol HOURS: Full time (35 hours) WORKING PATTERN: Our work style is hybrid, which involves spending at least two days…
At Urban Jungle , we’re making insurance fair - to people, planet and wallets. We're one of the fastest-growing businesses in the UK, working to fix one of the biggest industries in the world. We put customers at…
Data Engineer on a 12-month FTC building and maintaining scalable AWS data pipelines, containerised analytics apps, and IaC for a government client's multidisciplinary Data, Technology and Insights unit.
Lead Data Engineer (MLOps) defining technical direction and architecture, coding hands-on, and mentoring engineers to deliver scalable cloud-based Data Science & MLOps products using Python, SQL, cloud services, and containerisation.
Who are we? Look at the latest headlines and you will see something Ki insures. Think space shuttles, world tours, wind farms, and even footballers’ legs. Ki’s mission is simple. Digitally disrupt and revolutionise a…
Builds and optimizes cloud-based data pipelines (Databricks, Azure) for client projects, focusing on PySpark, SQL, and API ingestion while collaborating with stakeholders and maintaining infrastructure-as-code.
Full‑Stack Developer 6 month contract initially, with possibility of extension. Based onsite in Wokingham. Pay based on market rates per day via umbrella company. Overview We are looking for a skilled Azure .NET and…
Data Engineer at a Databricks-focused consultancy designing and building modern Lakehouse data platforms using Spark, Delta Lake, and cloud services for enterprise clients across financial services, retail, and the public sector.
Senior DevOps/MLOps engineer designing and maintaining cloud-native MLOps pipelines, Kubernetes-based AI/ML infrastructure, and CI/CD workflows for fintech applications, with a focus on AWS SageMaker, model governance, and Generative AI deployment.
Design and deploy secure, scalable multi-cloud solutions across AWS, Azure, and GCP, including landing zones, migrations, and observability, while enforcing security, governance, and FinOps practices.
GenAI Developer building and deploying LLM-based applications, RAG solutions, and AI-powered microservices on AWS (Bedrock, SageMaker, Lambda, ECS/EKS).
MLOps Engineer responsible for transitioning AI/ML models from experimentation to production, building CI/CD pipelines, monitoring/drift detection systems, and managing cloud and GPU infrastructure using Docker and Kubernetes.
Senior Data Solutions Engineer designing and implementing data engineering pipelines, advanced analytics, and modern data solutions (Lakehouse, data mesh, data fabric) using SQL, Python, and BI tools like Power BI in a hybrid role in South Africa.
The Forward Deployed Engineer embeds with clients to identify operational improvements and implement AI-driven solutions. This role bridges the gap between technical engineering and business consulting, managing the full lifecycle of AI product adoption.
Build and operate production AI model deployment platforms and MLOps tooling, handling model lifecycle management, inference pipelines, monitoring, and observability for batch and real-time AI workloads.
The AI Platform Engineer will build and maintain production infrastructure for AI models, focusing on deployment, monitoring, and automation within media workflows. The role utilizes MLOps practices, Python, and cloud technologies to ensure reliable, scalable AI service delivery.
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