1 to 25 of 28 Remote/Hybrid MLOps Jobs in the UK excluding London

enterprise. Work with a multi-functional team (DevOps, data engineers, developers, testers, Infosec) to productionize AI services on AWS. Enhance our tech stack, including MLOps, CI/CD pipelines, UI, and AI Python libraries. Develop prompts, fine-tune models, and track results. Evaluate third-party GenAI and LLM technologies ...

/CD and infrastructure as code. • Experience of optimising systems for performance and scalability and reliability. • Understanding of machine learning workflows or MLOps for deploying and monitoring models in production. • Experience with cloud platforms, especially AWS and its data services (e.g., BigQuery, Redshift, Athena). • Knowledge of network protocols ...

services. Apply data modelling concepts (e.g., medallion architecture) and ensure data quality and governance. Collaborate with DevOps teams to automate CI/CD and MLOps processes using Azure DevOps, Kubernetes, and Terraform. Visualize and communicate insights using Power BI, Tableau, and PowerApps. Mentor junior engineers and contribute to internal knowledge ...

move from legacy and hybrid platforms to a modern Fabric setup Supporting BI teams with semantic models, datasets and performance optimisation Enabling ML and MLOps workflows, from feature engineering to deployment Working closely with data scientists, analysts, IT and the wider business Embedding data quality, governance and best-practice standards ...

Terraform or Azure Bicep) to automate cloud deployments. CI/CD pipelines with Azure DevOps or GitHub Actions for automated deployment of data pipelines. MLOps best practices - MLflow, Databricks Model Serving, Feature Store. Knowledge of IFRS 17, BCBS 239, UK Data Protection Act and Solvency II compliance. Experience with pricing ...

priorities, work independently and collaborate effectively with stakeholders. Desirable Skills: Experience with Microsoft Fabric, Azure Machine Learning or similar enterprise cloud platforms. Exposure to MLOps practices, lifecycle management and large-scale or distributed compute environments. Familiarity with agentic AI concepts and frameworks such as LangChain, AutoGen or CrewAI, with ...

system design. Desirable (AI & Data) Vector DBs: Milvus, Weaviate, Pinecone Data orchestration: Airflow, Prefect, Dagster Search: ElasticSearch/OpenSearch AI frameworks: LangChain, Hugging Face MLOps: MLflow, Kubeflow If you are looking for an opportunity to work on mission-critical systems at the forefront of UK National Security? Apply ...

product-focused mindset, balancing experimentation with real-world value. Useful additional experience includes: AWS or GCP environments (SageMaker, Bedrock, Lambda, S3, Redshift). MLOps practices (monitoring, deployment, optimisation). Working with streaming data, transformer models or recommendation systems. What They Offer £70,000 to £90,000 salary. Hybrid working with ...

system design. Desirable (AI & Data) Vector DBs: Milvus, Weaviate, Pinecone Data orchestration: Airflow, Prefect, Dagster Search: ElasticSearch/OpenSearch AI frameworks: LangChain, Hugging Face MLOps: MLflow, Kubeflow If you are looking for an opportunity to work on mission-critical systems at the forefront of UK National Security? Apply ...

LLMs, NLP, or retrieval‐augmented workflows. • Confident working with large‐scale tabular datasets and complex data environments. • Cloud experience, ideally AWS, plus familiarity with MLOps practices. • Background in product‐focused environments or consultancy. • Ability to evidence measurable business impact from previous technical projects. What They Offer • Hybrid working with ...

automation Containerisation and orchestration Monitoring and observability tools Experience in the defence or advanced technology sector Experience with GPU based computer environments Experience with MLOps and associated tooling Experience with data pipelines Experience with Infrastructure as Code Experience with security integration in DevOps i.e. DevSecOps Service-oriented with effective communication ...

experience in training and deploying computer vision models into production · Proven track record with LLM fine-tuning, prompt engineering and productionisation · Deep experience in MLOps on Azure, including CI/CD, monitoring and scaling pipelines. · Strong coding skills in Python, with frameworks such as PyTorch, FastAPI and Azure CLI. ...

experience in training and deploying computer vision models into production · Proven track record with LLM fine-tuning, prompt engineering and productionisation · Deep experience in MLOps on Azure, including CI/CD, monitoring and scaling pipelines. · Strong coding skills in Python, with frameworks such as PyTorch, FastAPI and Azure CLI. ...

working in cloud environments, ideally Azure. Solid understanding of software engineering fundamentals including APIs, distributed systems and secure system design. Experience with DevOps or MLOps practices such as CI CD, containerisation and monitoring. The confidence and gravitas to influence technical direction and guide a less mature AI function. A practical ...

based and agent-driven AI systems using secure, governed data sources Develop scalable services on Azure, integrating with enterprise platforms and data pipelines Implement MLOps and AIOps capabilities including model lifecycle management, monitoring, and automation Embed security, compliance, and safety principles into every stage of development Collaborate within cross-functional ...

Preferred Experience with multimodal reasoning Experience with edge or offline AI deployments Familiarity with Kubernetes (EKS/OpenShift) for monitoring and managing deployed applications MLOps experience - model evaluation, monitoring, reproducibility Observability tooling for agentic systems (model drift, agent behaviour, performance monitoring) Experience with agent orchestration patterns and inter-agent communication ...

traditional ML solutions end-to-end Comfortable in startup or scale-up environments — fast-moving, iterative, delivery-focused Strong Python engineering experience Experience with MLOps, CI/CD, IaC, and productionising ML models Ability to work collaboratively with product, data, and engineering teams Contract Details Location: Hybrid London ...

iteration. Hands-on experience scaling a modern cloud data platform (lake/warehouse, orchestration, streaming). Deep understanding of the full ML lifecycle and MLOps/analytics engineering best practices. Experience implementing data architecture standards, data contracts, and governance across domains. Leadership experience managing managers and senior ICs within growing ...

models across: Natural Language Processing (NLP) Computer Vision Predictive/statistical modelling Own solutions from data preparation → training → evaluation → deployment Design and maintain robust MLOps pipelines (CI/CD for ML, model versioning, monitoring) Work closely with Data Engineers and DevOps to deliver scalable, production‐ready systems Shape ML architecture ...

predictive analytics — helping the world's largest employers find the right people, faster and fairer. But we're not done. Not even close. Role: MLOps Engineer Location: Remote Industry: Technology/AI & ML Infrastructure Job Function: MLOps/ML Platform Engineering Role Overview: We are hiring an MLOps Engineer ...

predictive analytics — helping the world's largest employers find the right people, faster and fairer. But we're not done. Not even close. Role: MLOps Engineer Location: Remote Industry: Technology/AI & ML Infrastructure Job Function: MLOps/ML Platform Engineering Role Overview: We are hiring an MLOps Engineer ...

Tune machine learning methods to best leverage our state-of-the-art processing capabilities Deploy and maintain machine learning methods in a DevOps/MLOps based machine learning environment Create robust high-quality code using test-driven development (TDD) techniques and adhering to the SOLID coding standards Your work will … Director of Technical Underwriting Propose, proof-of-concept, develop, and deliver novel machine learning processes that automate current manual processes, and leverage DevOps and MLOps software. Work in a collaborative environment with data science to help deploy machine learning methods that are state-of-the-art, robust, and future extensible. ...

business can trust and use data with confidence. You'll collaborate closely with colleagues in Data Engineering, Data Science, Pricing, Platform Engineering and MLOps, acting as a trusted partner and technical authority. Together, you'll define clear standards for how data is structured, governed and consumed, helping the organisation grow … Terraform or Azure Bicep) to automate cloud deployments. CI/CD pipelines with Azure DevOps or GitHub Actions for automated deployment of data pipelines. MLOps best practices - MLflow, Databricks Model Serving, Feature Store. Knowledge of IFRS 17, BCBS 239, UK Data Protection Act and Solvency II compliance. Experience with pricing ...

develop intelligent systems and tools Collaborating with cross-functional teams to integrate AI into production environments Conducting research, experimentation, and rapid prototyping Implementing MLOps best practices (CI/CD, monitoring, retraining pipelines) Translating business and stakeholder needs into scalable technical solutions Continuously improving AI/ML systems, frameworks, and performance … Experience building ML models using frameworks like PyTorch, TensorFlow, or scikit-learn Hands-on experience with LLMs (prompting, RAG, fine-tuning, agents) Understanding of MLOps principles and tools (e.g. MLflow, DVC, Weights & Biases) Experience deploying solutions in AWS or cloud environments Familiarity with Docker, CI/CD, and version control ...

develop intelligent systems and tools Collaborating with cross-functional teams to integrate AI into production environments Conducting research, experimentation, and rapid prototyping Implementing MLOps best practices (CI/CD, monitoring, retraining pipelines) Translating business and stakeholder needs into scalable technical solutions Continuously improving AI/ML systems, frameworks, and performance … Experience building ML models using frameworks like PyTorch, TensorFlow, or scikit-learn Hands-on experience with LLMs (prompting, RAG, fine-tuning, agents) Understanding of MLOps principles and tools (e.g. MLflow, DVC, Weights & Biases) Experience deploying solutions in AWS or cloud environments Familiarity with Docker, CI/CD, and version control ...