1 to 25 of 29 MLOps Jobs in the UK excluding London

and working experience of AGILE methodologies. Proficient with SQL. Familiarity with Databricks, Spark, geospatial data/modelling and insurance are a plus. Exposure to MLOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI etc are desirable We’ll help you gain Experience working in more »

in handling large datasets, experience with Azure Data Factory, Azure SQL Database, and Cosmos DB.Understanding of CI/CD pipelines, containerisation (Docker, Kubernetes), implementing MLOps practices using Azure DevOps. Azure Cloud services relevant to AI, such as Azure Kubernetes Service (AKS), Azure GPU VMs, and Azure networking and security services more »

agile working environment, with a focus on iterative and collaborative project delivery. Have worked with data visualisation tools e.g. Tableau. Experience in model monitoring. (MLOPS experience would be desirable.) Have gained a master's or Ph.D. in a quantitative field such as Computer Science, Statistics or related disciplines. Package Description more »

for people that are comfortable with terms like; Statistical Models, Computer Vision, Predictive Analytics, Data Visualization, Large Language Models (LLM), NLP, AI, Machine Learning, MLOPs, Python, Pyspark, and Azure. Flexible Working : The role is 60% work from home Sponsorship : Sadly sponsorship isn't available for these roles. About You: Bachelors more »

MLOps. Responsibilities Design and implement both Data Pipelines for both structured and unstructured data. Support and improve ML infrastructure – particularly Azure ML. Contribute to MLOps across the organisation. Requirements An academic background in Statistics, Mathematics, or Computer Science (or similar) A number of years of commercial work as a Senior more »

Data Engineers, as well as Cloud Software Engineers and DevOps in a Scrum environment. You can support streamlining deployment and establish best practices in MLOps for large models to build a better future where a new job is just a click away. Your responsibilities: Implement and productionise ML-based services more »

overall security posture of AI/ML and other business systems. Develop and maintain relationships between data scientists, data engineers, developers, operations (DevOps, DataOps, MLOps) and business unit leaders to govern and support scalability of the ML and AI initiatives. Key Skills Required: Solid understanding as a Security Architect, with more »

overall security posture of AI/ML and other business systems. Develop and maintain relationships between data scientists, data engineers, developers, operations (DevOps, DataOps, MLOps) and business unit leaders to govern and support scalability of the ML and AI initiatives. Key Skills Required: Solid understanding as a Security Architect, with more »

Experience: Experience in implementing production machine learning systems in a commercial environment. DevOps Knowledge: Good knowledge of DevOps in a Data Science context (e.g., MLOps) is a plus.Why Join Us? Innovative Environment: Work with cutting-edge technology in a dynamic and innovative environment. Impactful Work: Contribute to the safety and more »

with non-technical colleagues. Strong knowledge of Python and ML libraries (PyTorch, Tensorflow, Keras, etc.) with R/SQL knowledge, partnered with experience with MLOps tools (Kubernetes, Docker, Jenkins, etc.) would be advantageous. Strong knowledge and experience in deploying models into business processes, preferably in the healthcare, insurance or financial more »

a Machine Learning Engineer to join our Defence business unit. In this role, you will design, build, and deploy production-grade software, infrastructure, and MLOps systems that leverage machine learning. Your work will help solve a broad range of high-impact problems in the defence and national security space. Key more »

Desktop applications written in Windows Presentation Foundation using ReactiveUI and/or ASP.NETCore web services Good understanding of Git Experience of Machine Learning Operations (MLOps) Practical understanding of computational statistics Good communication skills, including the ability to explain technical concepts to users Experience of working on multiple projects in parallel more »

command of Python and its data analysis libraries (e.g., numpy, scipy) Proven expertise in Python-based machine learning, optimization, and process mining Knowledgeable about MLOps principles, CI/CD, model versioning, monitoring, and deployment Competent in utilizing Linux, Docker, AWS, Kafka, and git Consistent practice of best software development methodologies more »

RLHF), as well as optimised training procedures (e.g. QLora & Adapters) Comfortable with the machine learning lifecycle from research to deployment. This includes all things MLOps - model development, validation, deployment and monitoring Familiarity with state of the art NLP - text embeddings (representation learning), vector databases, large language models, machine translation, intent more »

will be the Senior Product Manager for a group of cross-functional Data Platforms teams within Oxa, incorporating the following key teams: Data Engineering; MLOps; Replay/Simulation as a Service; and Telemetry & Metrics. These teams are located in both our Oxford, UK HQ & Toronto, CA offices and support the more »

A fantastic opportunity has arisen for an experienced professional to join a distribution market leader as DevOps/MLOps Engineer at their site based in Leicester. You will work a hybrid role, with 3 days at home and 2 days in the office, working core hours Monday to Friday. As … a DevOps/MLOps Engineer you will be operationalising machine learning effectively. You will support the architectural needs of their Data Science team to ensure the seamless deployment, monitoring, and maintenance of machine learning models and data pipelines. You will work in close collaboration with the Data Science team to … position, you will develop and maintain automation scripts and tools to streamline the machine learning model deployment process and ensure reproducibility. The DevOps/MLOps Engineer will implement security best practices and ensure compliance with relevant data privacy regulations in all processes as well as work cross-functionally with Data more »

an ML approach. Create and productionise machine learning models using python, ML libraries, and Databricks. Process large scale data from our data lakehouse. Apply MLOps, AutoML, model explainability best practices. Present the results to stakeholders in an intuitive way and assisting the long-term tracking of the model performance to more »

an ML approach. Create and productionise machine learning models using python, ML libraries, and Databricks. Process large scale data from our data lakehouse. Apply MLOps, AutoML, model explainability best practices. Present the results to stakeholders in an intuitive way and assisting the long-term tracking of the model performance to more »

environments. Hands-on experience with cloud-based AI and ML solutions (e.g. Azure). Knowledge of generative AI applications and embedding models. Proficiency in MLOps and DevOps practices. Strong programming skills in Python and C#. Experience with Big Data technologies and ETL processes. Familiarity with distributed computing frameworks like Kubernetes. more »

application. These include ingesting and understanding new data sources, evolving our data approach (e.g., to a fully fledged data fabric), implementing containers to streamline MLOps and exploring how we can sensibly and safely utilise artificial intelligence (AI) to turbo charge our work (e.g., smart data quality monitoring, meta data curation … desirable Utilising AI within data engineering to drive performance. Knowledge of implementing, managing and utilising graph databases (e.g., using technologies such as Neo4j). MLOps experience including familiarity with Docker and Kubernetes. Full data engineering cycle knowledge (tools and skills) for stream data. Benefits Competitive salary and rewards package including more »

visualization tools (e.g., Tableau). - Basic statistical analysis knowledge. - Experience in deploying production ML systems. - Familiarity with DevOps in a data science context (e.g., MLOps) is a plus. Tools currently being used; - Python3, Numpy, Scipy, Xgboost - CI/CD: GitHub Actions, Jenkins, Docker - MLOps: DVC, MLflow - BI: Terraform, Airflow, BigQuery more »

We're looking for a Lead Machine Learning Engineer join our Data Engineering team. As the Lead ML Ops Engineer, you will be at the forefront of innovation, leading a small team of skilled engineers to develop and deploy scalable more »

Realtime are extremely proud to be partnering with a global tech leader on their search for an experienced Machine Learning Engineering Manager to lead their agile ML Engineering team here in Belfast. This team are providing word class machine learning more »

MLOPS and Data Engineer Salary: Circa £45,000 - £65,000 Fixed Term Contract: 12 months This is a great role for someone who is looking to join the UK’s leading savings, retirement & insurance business. Our company purpose is to be with you today, for a better tomorrow. Over 15.5 more »

office. Responsibilities include participation in software planning, conducting thorough code reviews, and devising thorough test plans. The ideal candidate will collaborate closely with the MLOps team, tasked with deploying machine learning models on specialized systems like Nvidia Jetson. Key Responsibilities; * Lead the design, development, and implementation of software solutions, ensuring … improvement. * Ensure software compatibility across Windows, Linux, and macOS platforms, addressing platform-specific nuances and optimizing user experience for each platform. * Collaborate with the MLOps team to deploy machine learning models on non- embedded systems, including Nvidia Jetson systems. Manage model deployment, monitoring, and optimization in production environments. Qualifications & Experience … Knowledge of macOS is a plus. * Knowledge of mobile app development frameworks and platforms (e.g., iOS SDK, Android SDK) is a plus. * Experience in MLOps, including deploying machine learning models on non-embedded systems such as Nvidia Jetson systems. If interested, and you match the criteria above, please apply with more »