1 to 25 of 1,211 MLOps Jobs in the UK

advanced machine learning techniques, including graph-based processing, computer vision, natural language processing, and simulation modeling. Experience with generative AI and LLMs, such as LLamaIndex and LangChain Understanding of MLOps or LLMOps. Familiarity with Agile methodologies, preferably Scrum We are actively seeking candidates for full-time, remote work within the UK. #J-18808-Ljbffr More ❯

LLMs) and prompt engineering (eg, GPT, BERT, T5 family). Familiarity with on-device or edge-AI deployments (eg, TensorFlow Lite, ONNX, mobile/Embedded inference). Knowledge of MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar) for experiment tracking and model governance. Open-source contributions or published papers in top-tier AI/ML conferences (NeurIPS, ICML, CVPR, ACL More ❯

LLMs) and prompt engineering (e.g., GPT, BERT, T5 family). • Familiarity with on-device or edge-AI deployments (e.g., TensorFlow Lite, ONNX, mobile/embedded inference). • Knowledge of MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar) for experiment tracking and model governance. • Open-source contributions or published papers in top-tier AI/ML conferences (NeurIPS, ICML, CVPR, ACL More ❯

LLMs) and prompt engineering (e.g., GPT, BERT, T5 family). Familiarity with on-device or edge-AI deployments (e.g., TensorFlow Lite, ONNX, mobile/embedded inference). Knowledge of MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar) for experiment tracking and model governance. Open-source contributions or published papers in top-tier AI/ML conferences (NeurIPS, ICML, CVPR, ACL More ❯

job is brought to you by Jobs/Redefined, the UK's leading over-50s age inclusive jobs board. Description We are looking for highly skilled and experienced Senior MLOps Engineer to join our team. This role will be involved in designing, implementing, and maintaining robust and scalable machine learning pipelines. This person will possess a strong background in DevOps … tune ML models for performance and accuracy. • Understanding of statistical analysis and experimental design. • Proficiency in data visualization and interpretation of ML results. Job responsibilities Proven experience as an MLOps Engineer or in a similar role, with an excellent understanding of AI/ML lifecycle management. Strong experience deploying and productionising ML models. Familiarity with data engineering concepts, including data … pipelines, ETL processes, and big data technologies. Excellent problem-solving skills and the ability to troubleshoot complex issues in AI/ML systems. Technical Insight Skills with MLOps concepts and principles. Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization tools (e.g., Docker, Kubernetes). Proficiency in programming languages such as Python, experience with AI/ML frameworks More ❯

Description We are looking for highly skilled and experienced Senior MLOps Engineer to join our team. This role will be involved in designing, implementing, and maintaining robust and scalable machine learning pipelines. This person will possess a strong background in DevOps practices, machine learning principles, and cloud computing platforms. You will work closely with data scientists and software engineers to … tune ML models for performance and accuracy. Understanding of statistical analysis and experimental design. Proficiency in data visualization and interpretation of ML results. Job responsibilities Proven experience as an MLOps Engineer or in a similar role, with an excellent understanding of AI/ML lifecycle management. Strong experience deploying and productionising ML models. Familiarity with data engineering concepts, including data … pipelines, ETL processes, and big data technologies. Excellent problem-solving skills and the ability to troubleshoot complex issues in AI/ML systems. Technical Insight Skills with MLOps concepts and principles. Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization tools (e.g., Docker, Kubernetes). Proficiency in programming languages such as Python, experience with AI/ML frameworks More ❯

We are looking for a highly skilled and experienced Senior MLOps Engineer to join our team. This role will be involved in designing, implementing, and maintaining robust and scalable machine learning pipelines. This person will possess a strong background in DevOps practices, machine learning principles, and cloud computing platforms. You will work closely with data scientists and software engineers to … tune ML models for performance and accuracy. • Understanding of statistical analysis and experimental design. • Proficiency in data visualization and interpretation of ML results. Job Responsibilities • Proven experience as an MLOps Engineer or in a similar role, with an excellent understanding of AI/ML lifecycle management. • Strong experience deploying and productionizing ML models. • Familiarity with data engineering concepts, including data … pipelines, ETL processes, and big data technologies. • Excellent problem-solving skills and the ability to troubleshoot complex issues in AI/ML systems. Technical Insight • Skills with MLOps concepts and principles. • Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization tools (e.g., Docker, Kubernetes). • Proficiency in programming languages such as Python, experience with AI/ML frameworks More ❯

and network analysis for relationship mapping. Open-source contributions or research publications in relevant fields. Familiarity with cloud platforms (AWS, Azure, or GCP) for ML model deployment. Knowledge of MLOps practices and tools for experiment tracking. Experience with big data processing frameworks like Apache Spark. Knowledge of NoSQL databases (MongoDB, Elasticsearch) for handling unstructured data. Experience with data versioning and More ❯

and Experience Working knowledge of DevOps practices, including CI/CD pipelines, automated testing and agile methodologies. Proficiency in infrastructure as code (IaC) using tools like Terraform. Experience with MLOps tools, frameworks and practices. Education and Professional Skills Nice to have relevant Professional qualifications, such as; Azure AI Engineer Associate Azure Data Scientist Associate Or equivalent certs with AWS/ More ❯

And Experience Working knowledge of DevOps practices, including CI/CD pipelines, automated testing and agile methodologies. Proficiency in infrastructure as code (IaC) using tools like Terraform. Experience with MLOps tools, frameworks and practices. Education And Professional Skills Nice to have relevant Professional qualifications, such as; Azure AI Engineer Associate Azure Data Scientist Associate Or equivalent certs with AWS/ More ❯

and observability-either independently or in collaboration with other specialists. Optimize model pipelines for latency, scalability, and cost-efficiency , and support real-time and batch inference needs. Collaborate with MLOps, DevOps, and data engineering teams to ensure reliable model deployment and system integration. Stay informed on current research and emerging tools in LLMs, generative AI, and autonomous agents , and evaluate More ❯

and observability—either independently or in collaboration with other specialists. Optimize model pipelines for latency, scalability, and cost-efficiency, and support real-time and batch inference needs. Collaborate with MLOps, DevOps, and data engineering teams to ensure reliable model deployment and system integration. Stay informed on current research and emerging tools in LLMs, generative AI, and autonomous agents, and evaluate More ❯

Excellent project management and time management skills, with the ability to manage complex, detailed work and effectively communicate progress and results to stakeholders at all levels Desirable: Experience with MLOps, including integration of machine learning pipelines into production environments, Docker, and containerization/orchestration (e.g., Kubernetes) Experience in deep learning development using TensorFlow or PyTorch libraries Experience with Large Language More ❯

GPT4 Omni, Qwen-vl, DocOwl etc.) for understanding complex documents and images. Experience in training, evaluating and hosting open source LLMs would be a major benefit. Some experience with MLOps would be very beneficial Full-stack development experience Experience with UI technologies like React would be helpful Experience with building search applications using Azure Search, Sinequa, Elastic or anything Lucene More ❯

Join to apply for the MLOps Field Engineer role at Canonical 2 weeks ago Be among the first 25 applicants Join to apply for the MLOps Field Engineer role at Canonical Get AI-powered advice on this job and more exclusive features. Canonical is a leading provider of open source software and operating systems to the global enterprise and technology … four times yearly in person, in interesting locations around the world, to align on strategy and execution. The company is founder-led, profitable, and growing. We are hiring an MLOps Field Engineer to help global companies embrace AI/ML in their business, using the latest open source capabilities on public and private cloud infrastructure, Linux and Kubernetes. Our team … traditional SQL databases and today's NoSQL data stores, as well as the machinery which turns data into insights and executable models. The people who love this role are MLOps engineers who enjoy customer conversations and solving customer problems during the presales cycle. They are solutions architects who like to solve customer problems through architecture, presentations and training. This role More ❯

operations throughout the United States as well as in Belfast. For more information, visit DailyPay's Press Center. The Role We are seeking a highly skilled and motivated Senior MLOps Engineer to join our growing team in Belfast. You will play a crucial role in maturing and scaling our machine learning infrastructure and processes, ensuring the reliability, scalability, and performance … of our ML models in production. This role requires a strong background in MLOps principles, cloud technologies (AWS), and a passion for building robust and efficient systems. You will collaborate closely with data scientists, engineers, and product teams to deliver high-quality ML solutions that directly impact our business. The mission of the Data Science Team is critical for the … development and success of our product, understanding the needs of our customers and partners, and maintaining DailyPay’s leading role in the early wage access industry. As a staff MLOps Engineer, you will be instrumental in helping to realize this vision for DailyPay by enabling efficient and effective deployment and management of machine learning models. How You Will Make An More ❯

with business stakeholders to create hypotheses, design and evaluate experiments and implement solutions that unlock significant business value in collaboration with teams such as Data Engineering, Machine Learning Operations (MLOps), Architecture, and Software Development. You’ll also proactively identify opportunities, providing the level of advanced analytics support needed for the problem and will provide technical thought leadership regarding the ethical … machine learning, AI and Generative AI modelling, and data science. You’ll support the operationalisation of machine learning and AI models by developing according to standards set by the MLOps framework. You’ll assist in the design and implementation of data pipelines and engineering infrastructure to embed scaled machine learning solutions. You’ll support the implementation of AI, GenAI and … support innovation. You’ll engage in group discussions on system design and architecture, sharing knowledge with the wider engineering community. You’ll collaborate closely with data scientists, data engineers, MLOps engineers, architects, and the software development team when developing solutions. You’ll liaise with stakeholders across the business to ensure ML is being used to improve strategic business decisions and More ❯

with clients to define their data science and ML strategies, ensuring alignment with business objectives and technical feasibility Lead the design, development, deployment and maintenance of ML models, emphasizing MLOps best practices for scalability and reliability Design and implement data pipelines to process, transform and prepare data for ML workflows Monitor, evaluate and improve model performance, addressing issues like data … formats like ONNX and TensorRT Proficiency in Python and ML/engineering frameworks such as PyTorch, TensorFlow (including Keras), Hugging Face (Transformers, Datasets) and scikit-learn, etc Experience with MLOps tools, including MLFlow, workflow orchestrators (Airflow, Metaflow, Perfect or similar), and containerisation (Docker) Strong knowledge of cloud platforms like Azure, AWS or GCP for deploying and managing ML models Familiarity More ❯

Marketing Group (OPMG). What You'll Focus On Leading the development of end-to-end pipelines for training, evaluating and deploying ML models to solve marketing problems Applying MLOps to operationalise ML models for clients’ marketing campaigns Supporting data scientists to build predictive models to improve media performance, customer experiences, revenue, and other outcomes across sectors like retail, telecoms More ❯

medium sized machine learning projects in small cross functional squads. What we’d like to see from you: Strong understanding of a wide range of ML algorithms. Understanding of MLOps practices for managing and monitoring models in production. Experience with deep learning frameworks (e.g. TensorFlow, PyTorch). Proficiency in programming languages such as Python, SQL and R. Knowledge of SQL More ❯

medium sized machine learning projects in small cross functional squads. What we’d like to see from you: Strong understanding of a wide range of ML algorithms. Understanding of MLOps practices for managing and monitoring models in production. Experience with deep learning frameworks (e.g. TensorFlow, PyTorch). Proficiency in programming languages such as Python, SQL and R. Knowledge of SQL More ❯

medium sized machine learning projects in small cross functional squads. What we’d like to see from you: Strong understanding of a wide range of ML algorithms. Understanding of MLOps practices for managing and monitoring models in production. Experience with deep learning frameworks (e.g. TensorFlow, PyTorch). Proficiency in programming languages such as Python, SQL and R. Knowledge of SQL More ❯

measurement. Collaborative Development: Work closely with marketing strategists, data analysts, data engineers, and product owners to define use cases and deliver scalable solutions. Model Deployment & Monitoring: Deploy models using MLOps practices and tools (e.g., MLflow, Airflow, Docker, cloud platforms) ensuring performance, reliability, and governance compliance. Innovation & Research: Stay current on advancements in AI/ML and proactively bring forward new More ❯

measurement. Collaborative Development: Work closely with marketing strategists, data analysts, data engineers, and product owners to define use cases and deliver scalable solutions. Model Deployment & Monitoring: Deploy models using MLOps practices and tools (e.g., MLflow, Airflow, Docker, cloud platforms) ensuring performance, reliability, and governance compliance. Innovation & Research: Stay current on advancements in AI/ML and proactively bring forward new More ❯

measurement. Collaborative Development: Work closely with marketing strategists, data analysts, data engineers, and product owners to define use cases and deliver scalable solutions. Model Deployment & Monitoring: Deploy models using MLOps practices and tools (e.g., MLflow, Airflow, Docker, cloud platforms) ensuring performance, reliability, and governance compliance. Innovation & Research: Stay current on advancements in AI/ML and proactively bring forward new More ❯