1 to 25 of 131 Remote MLOps Jobs in the UK excluding London

ML deployment, you will have the responsibility of managing projects with autonomy across the full data lifecycle. Responsibilities As an ML Engineer at Un:hurd music, you'll be: MLOps and Model Deployment : Own the deployment, maintenance, and retraining of machine learning models in production environments, designing scalable system architectures to ensure performance and resilience. Data Collection and Integration : Develop More ❯

testing, validation, deployment, to monitoring and retraining of models within different environments. If you've a strong understanding of Microsoft Azure, fluency in data science coding, and expertise in MLOps frameworks, we want to hear from you. Bring your excellent communication, problem-solving, and organizational skills to our team and help us drive innovation and excellence. This is a flexible … Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc You'll be skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management and organisation skills Ability to diagnose and troubleshoot problems quickly Excellent problem-solving and analytic … services, Event Hubs, Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc. Skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management and organisation skills Ability to diagnose and troubleshoot problems quickly Excellent problem-solving and analytic More ❯

testing, validation, deployment, to monitoring and retraining of models within different environments. If you've a strong understanding of Microsoft Azure, fluency in data science coding, and expertise in MLOps frameworks, we want to hear from you. Bring your excellent communication, problem-solving, and organizational skills to our team and help us drive innovation and excellence. This is a flexible … Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc You'll be skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management and organisation skills Ability to diagnose and troubleshoot problems quickly Excellent problem-solving and analytic … services, Event Hubs, Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc. Skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management and organisation skills Ability to diagnose and troubleshoot problems quickly Excellent problem-solving and analytic More ❯

in structured data querying and other business-specific applications Integrate LLMs with structured data systems (e.g., SQL databases, BigQuery, GCS) to enable natural language querying and advanced analytics. Implementing MLOps/LLMOps pipelines for deploying LLMs in production, monitoring their performance, and ensuring scalability. Evaluating LLM performance, optimising hyperparameters, and ensuring alignment with business objectives. Develop and maintain data integration … LangGraph, including prompt engineering, fine-tuning, and workflow orchestration. Skilled in integrating LLMs with structured data systems (e.g., SQL databases, BigQuery) to enable natural language querying and advanced analytics. MLOps/LLMOps Proficient in designing and implementing MLOps/LLMOps pipelines for model deployment, monitoring, version control, and CI/CD workflows. Strong understanding of model performance evaluation, hyperparameter tuning More ❯

and deploy advanced machine learning and behavioural intelligence models. Lead the transition of prototypes into scalable, cloud-native production systems. Architect data pipelines and model-serving infrastructure (Docker, Kubernetes, MLOps). Work with large-scale time series and behavioural data from diverse sensors. Contribute to strategic technical decisions and mentor junior engineers. Collaborate cross-functionally with product, UX, and leadership … Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for ML, and model performance monitoring. A background in behavioural biometrics, human-computer interaction, or large-scale sensor/time-series data is a strong plus. A More ❯

and deploy advanced machine learning and behavioural intelligence models. Lead the transition of prototypes into scalable, cloud-native production systems. Architect data pipelines and model-serving infrastructure (Docker, Kubernetes, MLOps). Work with large-scale time series and behavioural data from diverse sensors. Contribute to strategic technical decisions and mentor junior engineers. Collaborate cross-functionally with product, UX, and leadership … Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for ML, and model performance monitoring. A background in behavioural biometrics, human-computer interaction, or large-scale sensor/time-series data is a strong plus. A More ❯

and deploy advanced machine learning and behavioural intelligence models. Lead the transition of prototypes into scalable, cloud-native production systems. Architect data pipelines and model-serving infrastructure (Docker, Kubernetes, MLOps). Work with large-scale time series and behavioural data from diverse sensors. Contribute to strategic technical decisions and mentor junior engineers. Collaborate cross-functionally with product, UX, and leadership … Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for ML, and model performance monitoring. A background in behavioural biometrics, human-computer interaction, or large-scale sensor/time-series data is a strong plus. A More ❯

attribution, predicting customer propensity, segmenting customer groups based on behavioural data, and recommending products and/or content. Fine-tune Large Language Models to business-specific use cases. Deploy MLOps pipelines together with our ML engineers. Work closely with data engineers, fellow data scientists/AI engineers and consultants to ensure seamless integration and deployment of AI solutions that create … communication and problem-solving skills. Direct availability to start working in the UK. Nice to have: Experience with natural language processing (NLP) or computer vision (CV). Knowledge of MLOps and model deployment pipelines. Familiarity with AI ethics and responsible AI principles. Experience working with large datasets and distributed computing. Contributions to open-source AI projects. WE OFFER: The benefits More ❯

team helping to 'walk in the shoes' of application teams as well as operational engineering teams. Communicate progress, results, and insights to management and other stakeholders. Strong understanding of MLops principles and practices. Daily/Monthly Responsibilities Build and run responsibilities for GenAI ensuring robust support folding into standard incident processes as the products mature. Help work with distributed teams … and LLMs. An overall 8+ years of experience as Software Engineer. Proficiency in programming languages such as Python, TensorFlow, PyTorch, and other AI/ML frameworks. Strong understanding of MLops principles and practices. Ability to design and implement complex ML systems. Strong understanding of neural networks, natural language processing (NLP), computer vision, and other AI domains. Experience with cloud platforms More ❯

and Computer Vision Take ownership of developing, training and productionising machine learning lifecycles, adhering to best practices, security needs and quality assurance Development of neural networks Implementing and maintaining MLops workflows Work alongside Data Engineers and DevOps Engineers to ensure continuous integration and deployment of machine learning models in production. Proactive learning and researching new technologies and software versions Working … Knowledge of machine learning architectures, loss functions, tools and techniques Experience training machine learning models, including hyperparameter tuning and optimizing model performance Experience with (or at least exposure to) MLops workflows Experience with Python Experience with SQL Critical thinking and ability to problem solve Experience with data warehousing and database systems Exposure to working with CI/CD Knowledge of More ❯

tools and cloud platforms (e.g., Azure, GCP, AWS) Knowledge of deep learning, NLP, and computer vision techniques, (especially in the context of Microsoft Copilot and OpenAI APIs) Familiarity with MLOps practices using tools like Azure ML Pipelines, MLflow, Docker, and Kubernetes Excellent problem-solving and analytical skills, with the ability to apply AI to legal challenges Bachelor's or master More ❯

Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits: Competitive Salary & Bonus : £35,000 – £45,000 plus performance-based incentives Hybrid Working : A flexible mix of office and remote work Career More ❯

and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow More ❯

and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow More ❯

with cloud platforms like Microsoft Azure or Google Cloud Platform (GCP); familiarity with Databricks is a plus. Comfort working in cloud-based or secure environments, with an interest in MLOps or model deployment. Awareness and practice of responsible AI, data ethics, and governance frameworks. Willingness to explore emerging technologies such as agentic AI, GitHub Copilot, Microsoft Copilot and Copilot Studio. More ❯

advice and best practices to overcome these challenges and successfully deliver the expected business outcomes. Skills and experience required Experience in any related software/DevOps/DevSecOps/MLOps/AI roles within a regulated engineering environment. CI/CD deployment Software/AI development and deployment in complex programmes Strong Data and Application understanding with underpinning Infrastructure solution More ❯

Senior MLOps Engineer Hybrid/Dundee Salary up to £70,000 We are looking for a Senior MLOps Engineer to join a Scottish company working on cutting edge AI solutions. You will play a pivotal role in ensuring that ML initiatives drive value effectively while maintaining operational excellence. The Role: Managing and optimising existing ML model deployments to ensure reliability More ❯

scalable data science solutions, including predictive models, AI/ML-powered decision engines, and automation frameworks that deliver measurable commercial value. This includes integrating cloud-based, real-time, and MLOps best practices to ensure robust, production-ready solutions. Leading the end-to-end lifecycle of data science initiatives, this role will take solutions from ideation and prototyping to production deployment … Develop, deploy, and scale advanced data science solutions, including predictive models, AI/ML decision engines, and automation frameworks, to drive data-led operational decisions. Implement and oversee robust MLOps practices, ensuring models remain accurate, explainable, and optimized through continuous monitoring, retraining, and refinement. Champion responsible AI and governance, ensuring ethical, fair, and transparent AI/ML practices that align More ❯

end data science and analytics projects aligned with business priorities. Model Development : Build, test, and deploy predictive and optimisation models using Databricks, Azure, and Python , incorporating best practices in MLOps and governance. Insight Generation : Translate complex datasets into accessible and actionable insights using Power BI and other visualisation tools. Stakeholder Collaboration : Partner with cross-functional teams to embed analytics into … advanced analytics, or data engineering, with a track record of delivering measurable outcomes. Proficiency in Databricks, Azure, Python, SQL, and data visualisation using open source libraries. Experience with modern MLOps practices for deploying and maintaining models in production. Excellent communication skills - able to simplify technical concepts for varied audiences. Strong problem-solving skills and a focus on value creation over More ❯

with ML libraries and frameworks Solid understanding of statistical modelling, natural language processing (NLP), and/or deep learning Experience working with structured and unstructured data sources Familiarity with MLOps practices and tools (e.g., model versioning, CI/CD for ML, cloud deployment) Excellent communication and stakeholder engagement skills Bachelors or Masters degree in Computer Science, AI, Data Science, or More ❯

/conferences Experience with Git-workflow within a production team Experience with Agile product development Experience of working in a start-up Best practices in data engineering Familiarity with MLOps Experience with building Restful services Experience presenting in front of project stakeholders Keen business development interest Start date : Immediate Contract Type : Permanent Oxford Dynamics is committed to creating an inclusive More ❯

with cloud platforms like Microsoft Azure or Google Cloud Platform (GCP); familiarity with Databricks is a plus. Comfort working in cloud-based or secure environments, with an interest in MLOps or model deployment. Awareness and practice of responsible AI, data ethics, and governance frameworks. Willingness to explore emerging technologies such as agentic AI, GitHub Copilot, Microsoft Copilot and Copilot Studio. More ❯

with cloud platforms like Microsoft Azure or Google Cloud Platform (GCP); familiarity with Databricks is a plus. Comfort working in cloud-based or secure environments, with an interest in MLOps or model deployment. Awareness and practice of responsible AI, data ethics, and governance frameworks. Willingness to explore emerging technologies such as agentic AI, GitHub Copilot, Microsoft Copilot and Copilot Studio. More ❯

to complex business problems, with the goal of improving supply chain efficiency, optimise vehicle movement, and enhance operational workflows across the organisation. You’ll be supported by a modern MLOps and Data Engineering function, giving you the time and tools to focus on innovation , model development , and strategic delivery . Key Responsibilities Lead and mentor a data science team focused … mathematical optimisation techniques (e.g., Linear Programming , Scheduling , Graph Theory ) to complex business problems. Work cross-functionally with senior stakeholders to translate business requirements into scalable technical solutions. Collaborate with MLOps and Engineering teams to productionise models using robust and scalable pipelines. Champion the integration of model outputs into wider data and reporting platforms. Clearly communicate technical insights and model outcomes … functional squads. What You’ll Get in Return A leadership role where your work has direct and measurable impact on operational efficiency and bottom-line performance. Dedicated support from MLOps and Engineering teams to accelerate delivery. Access to career development support including coaching, mentoring, and leadership training . A competitive salary package including car allowance , bonus , and comprehensive benefits such More ❯

areas for improvements and updates. Passionate about work, output and quality. Curious and willing to onward develop and learn in ML/AI area. Desirable Criteria Benefits: Familiarity with MLOps principles Familiarity with Geospatial (GIS) data Familiarity and experience with agile development in delivery Experience in Automation/Testing frameworks Experience of Continuous Integration/Development and Tooling Experience of More ❯