1 to 25 of 33 Remote/Hybrid MLOps Jobs in the UK excluding London

control. Strong communication skills, especially with non-technical customers. Desirable (SEO-Optimised) Experience with cloud platforms (AWS, Azure, GCP). Docker/Kubernetes & modern MLOps tooling. Experience across NLP, tabular modelling or computer vision. Exposure to LangChain, vector databases or AI-augmented development workflows. Benefits 35 days leave, including public ...

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 ...

technical challenges Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related technical discipline Bonus Skills/Experience Understanding of MLOps, model serving, scaling and monitoring workflows (e.g., BentoML, MLflow, Vertex AI, AWS Sagemaker) Experience building streaming + batch data ingestion and transformation pipelines (Spark/ ...

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 ...

Mathematics Computer Science or a related quantitative discipline Desirable Skills for the Data Scientist: Experience with deep learning frameworks advanced modelling techniques Familiarity with MLOps concepts model monitoring deployment pipelines Exposure to tools such as Databricks MLflow feature stores Experience working in Agile product-led delivery environments Understanding of data ...

internal stakeholders Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment Experience of appropriate version control and environment management (such as venvs or Docker) Experience of writing technical project proposals ...

deep learning frameworks (TensorFlow, PyTorch) Solid understanding of ML algorithms, statistics, and data modelling Experience with large-scale data tools (Hadoop, Spark, Kafka) Cloud & MLOps experience (AWS, Azure, or GCP) NLP experience highly beneficial Strong leadership, communication, and stakeholder management ...

hypotheses through well-designed ML experiments. Hands-on experience creating and deploying AI/ML models , including Large Language Models (LLMs) . Understanding of MLOps principles and deploying models into production environments. Collaboration & Delivery Experience working within - and ideally leading - cross-functional teams . Ability to translate complex business challenges ...

architectures . Expert-level SQL and experience with BigQuery and vector databases (Pinecone, Weaviate, Vertex AI Search). Proven track record in MLOps and deploying ML models at scale. Experience moving LLM-based prototypes into production environments with thousands of users. Background in building internal tooling, CRM enhancements, or sales ...

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 ...

associated architecture patterns Experience designing and managing APIs including REST and GraphQL Strong understanding of microservices and serverless architectures Practical experience with DevOps and MLOps practices including CI/CD pipelines Knowledge of security frameworks, identity management and authentication standards Desirable Skills for the AI Solutions Architect: Experience with enterprise ...

globally. Key Responsibilities Research and develop state-of-the-art ML algorithms for network orchestration Build and manage ML training infrastructure using Kubernetes and MLOps tools Develop and maintain documentation for new algorithms and systems Integrate AI/ML solutions into the wider Spacetime platform Act as a technical expert ...

language models including prompt engineering, fine-tuning and evaluation Practical experience with core Generative AI frameworks and agent-based AI frameworks Strong experience with MLOps and LLMOps tooling including model lifecycle management Proven deployment experience on major cloud platforms including AI and ML services Solid foundation in software engineering principles ...

essential): Experience working with large language models via APIs or open-source frameworks. Fine-tuning or evaluating generative AI systems. Knowledge of MLOps, monitoring and lifecycle management. Experience with cloud AI/ML services and scalable data platforms. Exposure to reinforcement learning, graph machine learning or advanced deep learning techniques. ...

issues and implement effective resolutions. Optimize application performance using Azure monitoring tools (Azure Monitor, App Insights). Improve SQL query performance for applications and MLOps workflows. Perform proactive monitoring, troubleshooting, and enhancement of application functionality. Integration & Documentation Integrate third-party APIs/services ensuring seamless communication. Document technical decisions, architectural ...

Architect secure, scalable GenAI solutions on AWS and GCP Build APIs, services, and pipelines to integrate GenAI into real business workflows Apply LLMOps/MLOps practices : versioning, monitoring, cost control, bias, and drift management Work directly with clients to translate business problems into deployable AI solutions , not slide decks Contribute ...

Ability to clearly explain complex AI concepts to technical and non-technical stakeholders Desirable: Experience with cloud platforms (AWS, Azure, or GCP) Familiarity with MLOps, evaluation, and monitoring of AI systems Experience working in product-led or scale-up environments Reasonable Adjustments: Respect and equality are core values to us. ...

Ability to clearly explain complex AI concepts to technical and non-technical stakeholders Desirable: Experience with cloud platforms (AWS, Azure, or GCP) Familiarity with MLOps, evaluation, and monitoring of AI systems Experience working in product-led or scale-up environments Reasonable Adjustments: Respect and equality are core values to us. ...

concept to production Establish AI operating models, best practices, and responsible AI frameworks Build and lead high-performing multidisciplinary teams (Data Science, ML Engineering, MLOps) Identify use cases across functions (customer experience, operations, knowledge management, automation) Ensure scalability, security, and compliance of AI platforms Required Experience Proven leadership delivering Generative … deep learning, model optimisation Evaluation frameworks and guardrails Data & Platforms Vector databases (Pinecone, Weaviate, FAISS, Milvus) Knowledge graphs and semantic search Data engineering pipelines MLOps & Deployment CI/CD for ML, model monitoring, versioning Kubernetes, Docker, serverless architectures MLflow, Kubeflow, SageMaker or similar Cloud & Architecture Azure AI, AWS AI/ ...

MLOps Engineer London Based - Hybrid (Three days per week on site)£90,000 to £110,000 plus bonus This is an exciting opportunity to join a mission driven cleantech scale up as they continue to grow their data and AI function. You will help shape a modern MLOps environment, working … would be joining a small, high impact data group with experienced engineers and the opportunity to take real ownership. The Role In this MLOps Engineer role, you will contribute to the design, deployment and optimisation of production ML systems. Responsibilities include: Supporting data scientists and AI engineers to build, deploy ...

cloud computing (ideally AWS) Strong experience across industries in both Geospatial and non-Geospatial domains Experience with Machine Learning (sci-kit learn, tensorflow, metaflow, MLOps) Preferred Experience: Experience with frameworks like Metaflow, Prefect, etc. Experience with geospatial libraries i.e. Raster, Geo-pandas, Vector databases Bright Purple is an equal opportunities ...

communicate solutions that enable data- and AI-driven business outcomes. This role supports the organisation in maximising productivity and innovation through reliable AI platforms, MLOps practices, and cloud-based digital transformation initiatives. What you’ll be doing: As a Digital and AI Support Apprentice, you will be supported to: Adopt ...

background) Experience building products from 0-1 , ideally in a startup or scale-up Comfortable working on APIs, cloud/infra products, or MLOps tooling Kubernetes An AI power user actively experimenting with multiple tools Confident individual contributor with strong stakeholder skills Strong experience in decentralised/blockchain environments Working ...

services. AI & ML Leadership Architect advanced Data Science, ML and AI solutions, including NLP, RAG LLM and Agentic AI systems. Oversee the implementation of MLOps frameworks, ensuring robust deployment, monitoring, and lifecycle management of ML models. Evaluate and recommend emerging AI/ML technologies and platforms, driving innovation in intelligent … data governance, and quality frameworks. Implementing technical reviews and driving high standards. Collaborate with engineering and DevOps teams to establish CI/CD and MLOps architectures using Azure DevOps, Kubernetes, and Terraform. Guide the selection and implementation of visualization and analytics tools (Power BI, Tableau, PowerApps). Stakeholder Engagement: Engage ...

using both classical ML and generative AI. Integrate AI into digital products through services, APIs, and safe, compliant guardrails. Manage model life cycle and MLOps while sharing best practices and enabling colleagues. Skills and Experience The successful AI Engineer will have the following skills and experience: Strong Python … experience, ideally with Databricks Experience with ML and LLM tools (e.g., scikit learn, XGBoost, PyTorch, TensorFlow, RAG, APIs) Comfortable with data engineering basics and MLOps practices Experience working with cloud platforms such as Azure, AWS, or GCP Benefits The successful Senior AI Engineer will receive the following benefits: Salary ...