1 to 25 of 103 Permanent MLOps Jobs in the UK excluding London

Edinburgh, United Kingdom Posted on 01/07/2025 Are you a DevOps engineer ready to dive into the world of MLOps? Do you want to work on real-world deployments of cutting-edge machine learning models, including Large Language Models (LLMs)? We're looking for a motivated Junior MLOps Engineer with a DevOps background, eager to help us … deploy and maintain machine learning models, especially Large Language Models (LLMs), in production environments. If you have solid DevOps experience and are keen to grow your MLOps skills, we'd love to hear from you! About Aveni Aveni is an award-winning technology company. We use advanced AI to enable scalable efficiency for financial services companies, combining world-leading Natural … CD for ML pipelines Developing production-grade APIs (REST/gRPC) to serve models Collaborating with engineers, data scientists & DevOps teams Requirements Your Experience Industry experience in DevOps or MLOps roles (ideally in AWS environments) Hands-on with Docker, Kubernetes, and Terraform Strong scripting skills in Python or Bash Familiar with ML lifecycle tools, model monitoring, and versioning Exposure to More ❯

Date: July 2025 Company: Fuzzy Labs Job Title: Lead MLOps Engineer Location: Central Manchester Working style: Hybrid Fuzzy Labs are a Manchester based startup that helps our clients productionise machine learning through Open Source MLOps. We exist to help harness and channel the power of AI more quickly, to make positive change and use AI for good. We are growing … our team of engineers to help deliver an increasing number of client projects. You won't need an existing MLOps background to apply for this role. You'll learn as you go by immersing yourself in this exciting new field. What we're looking for We've seen considerable growth over the past few years and this will continue as … we build on our reputation as Open Source MLOps experts, while working with the community, and delivering solutions to our clients. The ideal candidate would be motivated to grow and progress in line with the company's ambitions. As well as being a great engineer, motivated by the chance to be at the forefront of MLOps adoption, you'll also More ❯

Date: July 2025 Company: Fuzzy Labs Job Title: MLOps Engineer Location: Central Manchester Working style: Hybrid Fuzzy Labs are a Manchester based startup that helps our clients productionise machine learning through Open Source MLOps. We exist to help harness and channel the power of AI more quickly, to make positive change and use AI for good. We are growing our … team of engineers to help deliver an increasing number of client projects. You won't need an existing MLOps background to apply for this role. You'll learn as you go by immersing yourself in this exciting new field. What we're looking for We've seen considerable growth over the past few years and this will continue as we … build on our reputation as Open Source MLOps experts, while working with the community, and delivering solutions to our clients. The ideal candidate would be motivated to grow and progress in line with the company's ambitions. As well as being a great engineer, motivated by the chance to be at the forefront of MLOps adoption, you'll also enjoy 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 ❯

Senior Data Scientist (Natural Language Processing) Total Remuneration: £57,879 to £68,146 Pay Supplement: The base salary for this role is £46,677 - £54,957 This job qualifies for Digital, Data and Technology Annual Pay supplement of 24% which 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 ❯

60k per annum As a Machine Learning Engineer , you will be part of an MLOps team, working alongside data scientists, software engineers, and other stakeholders to bring machine learning models to life. You will be responsible for deploying, maintaining, and monitoring models in production, improving model performance, and refining the machine learning infrastructure to support business objectives. Your role will More ❯

real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed data tools (Spark, etc.). Strong written and verbal communication skills, especially More ❯

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. 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, and maintenance using tools like Vertex AI Pipelines. More ❯

Senior ML & AI Backend Developer You'll lead the design and deployment of scalable backend systems powering ML, big data, and LLM-driven applications. From MLOps pipelines and big data engineering to productionizing classical ML and LLMs, you'll be at the core of AI infrastructure. Key Requirements: Expert in Python, ML/AI frameworks (PyTorch, TensorFlow, Hugging Face) Proven … MLOps, big data, and backend/API development experience Deep understanding of NLP and LLMs Proficient with cloud platforms (AWS/GCP/Azure), Airflow, DBT, Docker/Kubernetes Strong collaboration, problem-solving, and coding best practices Nice to have: LLM fine-tuning, streaming data, big data warehousing, open-source contributions. 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 ❯

MLOps Engineer London£60,000-£70,000 About the Role: Join a cutting-edge technology company at the forefront of immersive experiences powered by machine learning and extended reality. We are seeking a skilled MLOps Engineer to help build, deploy, and maintain scalable machine learning infrastructure that drives innovation in our products. You will play a critical role in developing … scalable ML infrastructure that powers immersive XR applications with real-time 3D content. Key Responsibilities: Design, develop, and maintain scalable MLOps pipelines tailored for XR applications, ensuring smooth deployment and monitoring of machine learning models. Collaborate closely with 3D artists and XR developers to integrate machine learning workflows with 3D rendering engines. Optimize ML models and workflows for real-time … related to ML inference and 3D rendering workloads. Develop monitoring solutions to track model performance and system health in production. Stay up to date with the latest trends in MLOps, XR technologies, and 3D rendering techniques to propose innovative improvements. Qualifications: Proven experience as an MLOps engineer or similar role with a focus on 3D applications Strong programming skills in More ❯

data science can deliver measurable value. Create powerful visualisations and present findings to technical and non-technical stakeholders. Build, deploy, and maintain robust data pipelines and production-grade models (MLOps). Champion ethical data practices, governance, and high-quality documentation. Stay up to date with AI and data science innovations, bringing cutting-edge thinking into the business. Experience required A … e.g., TensorFlow, PyTorch, Scikit-learn). Strong skills in data storytelling, problem-solving, and working with both structured and unstructured data. Experience with APIs, cloud platforms (especially AWS), and MLOps practices is a strong advantage. A collaborative, curious mindset with excellent communication skills and a passion for innovation. Benefits include: Salary £55,000 dependant on experience Hybrid working, two days More ❯

experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn) Solid understanding of machine learning algorithms and statistical methods Experience working with cloud platforms (AWS, GCP, or Azure) Familiarity with MLOps tools and practices is a plus A degree in Computer Science, Engineering, Mathematics, or a related field What We Offer Salary: £50,000–£60,000 depending on experience Hybrid working More ❯

Physics, or related fields 4+ years Systems Engineering or related experience 2+ years experience with CV, NLP, and LLM architectures Knowledge of large-scale software architectural patterns Experience with MLOps, automation tools, containerization (Docker, Kubernetes), and ML lifecycle management Knowledge of Rust is a plus Experience with fine-tuning GenAI models and Reinforcement Learning is a plus Customer focus and 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 ❯

AI Development Platform Engineer 6 Month Contract (Inside IR35) Hybrid, Glasgow (3 days PW) Starting ASAP Day Rate: £545 About the Role: This role is for a platform engineer who will help build a firmwide AI Development Platform and drive More ❯

changes. We welcome open-minded developers who like to share knowledge and help each other to push Optimove forward using the cutting edge of today's tech. The new MLOps team will be responsible for the seamless deployment, monitoring, and maintenance of machine learning models in production. Acting as the critical link between the data science and R&D teams More ❯

data scientists and engineers across multiple projects Oversee the deployment and monitoring of machine learning models in production Define coding standards and implement best practices in CI/CD, MLOps, and API delivery Collaborate with business, product, and engineering teams to align data strategy with commercial goals Champion data governance, security, and compliance throughout the data lifecycle Evaluate and introduce … data platform architecture Proven leadership within technical teams, ideally in cloud-first environments (Azure, AWS, or GCP) Proficiency in Python, SQL , and cloud-native data tools Solid understanding of MLOps , including model lifecycle management (e.g. MLflow), containers (Docker/Kubernetes), and monitoring Experience delivering Data-as-a-Service products and APIs Excellent communication skills - able to explain complex concepts to 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 ❯