4 of 4 Containerisation Jobs in Watford

ll be working on: Azure platform improvements + AWS crossover (GCP experience a bonus) Migrating VMs, databases, and networks from datacentres Infrastructure as Code (Terraform) Automation with PowerShell & Python Containerisation (Docker, Kubernetes) Documentation & project ownership You'll bring: Proven experience managing cloud platforms (Azure, AWS, GCP) Strong Terraform, PowerShell & Python skills Experience with Docker and Kubernetes DevOps background, ideally from More ❯

ETL and data exchange experience (e.g. APIs, ESB tools) Knowledge of Big Data (e.g. Hadoop) Curiosity about AI, particularly NLP, OCR or Generative AI 🌟 Bonus Points For Docker/containerisation experience Any previous work in industrial, aerospace or secure environments Exposure to tools like LLMs, OCR engines, or knowledge graphs 💰 What's On Offer Salary up to £55,000 + More ❯

week Start: ASAP Duration: 6 - 12 months Rate: £540 per day, inside IR35 Were looking for an HPC Technical Lead with deep expertise in High-Performance Computing platforms , Docker containerization , Azure infrastructure , and Linux systems . This role is ideal for a technical leader who thrives in designing, building, and managing cutting-edge HPC environments. Key Responsibilities Lead the technical … methodologies . Why Join? This is an exciting opportunity to lead technical innovation within HPC, working on impactful projects at scale. Youll have the chance to shape infrastructure, implement containerization best practices, and drive modernization in a highly collaborative environment. If you have the relevant skills and experience, please apply promptly and we will be in touch to discuss your More ❯

with a variety of structured and unstructured datasets, handling preprocessing, cleaning, and feature engineering. Develop pipelines for creating, preparing, and optimising data for modelling. Deploy models to production using containerisation tools (Docker, Kubernetes) and ensure scalability, robustness, and monitoring. Research and apply the latest advancements in Generative AI and data science. Support model evaluation, logging, and performance tuning across GPU … Proficiency in Python (essential) and familiarity with relevant libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch). Experience with prompt engineering and model evaluation. Deployment experience using Docker or other containerisation tools. Exposure to GPU-based environments for large-scale model training and tuning. Experience with big data tools (Spark, Hadoop) and cloud platforms (AWS, GCP, Azure) is a plus. Strong More ❯