76 to 100 of 337 MLOps Jobs in the UK

cross-functional working environment Possess a clear passion for data science beyond the day job Nice-to-haves: NLP, OpenCV, Generative AI, data visualization, MLOps On offer : Base salary of £85k - £95k depending on experience Hybrid working - 3 days in the Bristol office More ❯

Experience in a fast-paced, product-driven startup environment Experience with Golang Experience in the autonomous retail industry or a similar domain Experience in MLOps, DevOps, and build/release/deployment automation. More ❯

development ✔ Strong Python, SQL, and Databricks skills (especially PySpark & Delta Lake) ✔ Deep experience with Azure: Data Factory, Synapse, Event Hub, Azure Functions ✔ Understanding of MLOps tooling like MLflow and integration with AI pipelines ✔ Exposure to data for LLM workflows, unstructured sources, and real-time ingestion ✔ Comfortable operating in an early More ❯

development ✔ Strong Python, SQL, and Databricks skills (especially PySpark & Delta Lake) ✔ Deep experience with Azure: Data Factory, Synapse, Event Hub, Azure Functions ✔ Understanding of MLOps tooling like MLflow and integration with AI pipelines ✔ Exposure to data for LLM workflows, unstructured sources, and real-time ingestion ✔ Comfortable operating in an early More ❯

processes Familiarity with cloud platforms, particularly Microsoft Azure Understanding of microservices architecture and distributed systems Experience with DevOps practices for AI/ML workflows (MLOps) Strong programming skills in Python and related data science libraries Demonstrated ability to work within solution architecture frameworks Other preferred skills Experience with multiple cloud More ❯

processes Familiarity with cloud platforms, particularly Microsoft Azure Understanding of microservices architecture and distributed systems Experience with DevOps practices for AI/ML workflows (MLOps) Strong programming skills in Python and related data science libraries Demonstrated ability to work within solution architecture frameworks Other preferred skills Experience with multiple cloud More ❯

concepts. Excellent programming skills in Python. Demonstrated experience in building, validating, deploying, monitoring, and updating production ML and AI models. Hands-on experience with MLOps and AIOps infrastructure and tooling. Proficient in problem-solving and analytical reasoning. Exceptional communication and collaboration skills. Experience with ML frameworks such as TensorFlow, PyTorch More ❯

to-Have: Experience with marketing data or customer-level modelling (e.g., uplift, attribution, causal AI, graph AI, campaign optimization, spend optimization). Exposure to MLOps tools like MLflow, FastAPI, Airflow, or similar. Experience with experimentation and validation frameworks (e.g., A/B testing). Startup or freelance experience that required More ❯

Kafka. Strong understanding of SQL, NoSQL, and data modeling. Familiarity with cloud platforms (AWS, Azure, GCP) for deploying ML and data solutions. Knowledge of MLOps practices and tools, such as MLflow or Kubeflow. Strong problem-solving skills, with the ability to troubleshoot both ML models and data systems. A collaborative More ❯

Kafka. Strong understanding of SQL, NoSQL, and data modeling. Familiarity with cloud platforms (AWS, Azure, GCP) for deploying ML and data solutions. Knowledge of MLOps practices and tools, such as MLflow or Kubeflow. Strong problem-solving skills, with the ability to troubleshoot both ML models and data systems. A collaborative More ❯

or digital transformation • Certification in MS Azure or AWS Cloud data engineering or similar track • Understanding of the Software Development Life Cycle, Devops and MLOPS • Strong skills in one object orientated language • Excellent presentation skills • Understanding application of project mgmt. and agile methodologies What we look for We're interested More ❯

an emphasis on vision. Proficiency with deep learning frameworks such as TensorFlow/PyTorch. Proficiency with Python and strong software development background. Experience with MLOps practices, including versioning, deployment, and monitoring of models highly desirable. Ability to communicate complex technical concepts clearly to non-technical stakeholders. Why Work for Proximie More ❯

in the field. You'll join a global team with a distributed set of skills including Research, Applied AI and Engineering. They are seeking MLOps Engineers to help architect the future of communication through AI. This isn't just another engineering role – it's an opportunity to pioneer systems that … transform how companies connect with their customers What You’ll Be Doing You'll be designing and optimising production-grade MLOps pipelines that bring cutting-edge Generative AI and LLMs from experimentation to real-world impact. Your expertise will directly influence how some of the world's leading brands enhance … their strategies. What You'll Build Production-Ready GenAI Infrastructure : Design and deploy scalable MLOps pipelines specifically optimized for GenAI applications and large language models State-of-the-Art Model Deployment : Implement and fine-tune advanced models like GPT and similar architectures in production environments Hybrid AI Systems : Create solutions More ❯

in the field. You'll join a global team with a distributed set of skills including Research, Applied AI and Engineering. They are seeking MLOps Engineers to help architect the future of communication through AI. This isn't just another engineering role – it's an opportunity to pioneer systems that … transform how companies connect with their customers What You’ll Be Doing You'll be designing and optimising production-grade MLOps pipelines that bring cutting-edge Generative AI and LLMs from experimentation to real-world impact. Your expertise will directly influence how some of the world's leading brands enhance … their strategies. What You'll Build Production-Ready GenAI Infrastructure : Design and deploy scalable MLOps pipelines specifically optimized for GenAI applications and large language models State-of-the-Art Model Deployment : Implement and fine-tune advanced models like GPT and similar architectures in production environments Hybrid AI Systems : Create solutions More ❯

wide range of AI models which underpin our platform. This includes specific expertise in emerging methods for Graph-based models and NLP models. Our MLOps team is tasked with automating and maximizing efficiency of the build, deployment and maintenance of all model types. We are seeking a Senior MLOps Engineer … to join our team. This individual will play a crucial role in designing, deploying, and maintaining production-level machine learning models. The Senior MLOps Engineer will focus on leading MLOps initiatives, including infrastructure, automation, and ensuring models are seamlessly transitioned from development to production. The role demands technical expertise in … MLOps and experience in collaborating with remote teams. Responsibilities Establish the Quantexa ML Ops team and the team's interfaces to other parts of Quantexa. Advance our approaches to deployment of ML models within our platform. Work with Architects and DS teams to select appropriate model architectures and patterns, including More ❯

learn. Expert-level experience in Power BI for advanced visualisations, ML model interpretation, and KPI tracking. Deep knowledge of feature engineering, model deployment, and MLOps best practices. Experience with big data processing (Spark, Hadoop) and cloud-based data science environments. Other: Ability to integrate ML workflows into large-scale data More ❯

systems Practical experience with LLMs and their applications Proficiency in Python and ML frameworks (TensorFlow, PyTorch, etc.) Knowledge of containerization, CI/CD, and MLOps practices More ❯

systems Practical experience with LLMs and their applications Proficiency in Python and ML frameworks (TensorFlow, PyTorch, etc.) Knowledge of containerization, CI/CD, and MLOps practices More ❯

learn. Expert-level experience in Power BI for advanced visualisations, ML model interpretation, and KPI tracking. Deep knowledge of feature engineering, model deployment, and MLOps best practices. Experience with big data processing (Spark, Hadoop) and cloud-based data science environments. Other: Ability to integrate ML workflows into large-scale data More ❯

years in Data Science/ML Engineering 2+ years hands-on with Databricks Strong track record delivering production-grade ML models Solid grasp of MLOps best practices Confident speaking to technical and non-technical stakeholders 🛠️ Tech you’ll be using: Python, SQL, Spark, R MLflow, vector databases GitHub/GitLab More ❯

years in Data Science/ML Engineering 2+ years hands-on with Databricks Strong track record delivering production-grade ML models Solid grasp of MLOps best practices Confident speaking to technical and non-technical stakeholders 🛠️ Tech you’ll be using: Python, SQL, Spark, R MLflow, vector databases GitHub/GitLab More ❯

such as Scikit learn, Keras, Tensor flow, and PySpark. Experience and understanding of mixed technical teams such as engineering, architects, business analysts. Familiar with MLOps industry best practices. Good stakeholder communication skills with proven ability to translate complex scientific findings to non-technical stakeholders. Understanding of the financial industry, in More ❯

such as Scikit learn, Keras, Tensor flow, and PySpark. Experience and understanding of mixed technical teams such as engineering, architects, business analysts. Familiar with MLOps industry best practices. Good stakeholder communication skills with proven ability to translate complex scientific findings to non-technical stakeholders. Understanding of the financial industry, in More ❯

such as Scikit learn, Keras, Tensor flow, and PySpark. Experience and understanding of mixed technical teams such as engineering, architects, business analysts. Familiar with MLOps industry best practices. Good stakeholder communication skills with proven ability to translate complex scientific findings to non-technical stakeholders. Understanding of the financial industry, in More ❯

such as Scikit learn, Keras, Tensor flow, and PySpark. Experience and understanding of mixed technical teams such as engineering, architects, business analysts. Familiar with MLOps industry best practices. Good stakeholder communication skills with proven ability to translate complex scientific findings to non-technical stakeholders. Understanding of the financial industry, in More ❯