26 to 50 of 357 MLOps Jobs in the UK

of machine learning algorithms, statistics, and predictive modeling Proficiency with Python and machine learning toolkits like pandas, scikit-learn, and optionally pytorch/tensorflow. Experience with machine learning operations (MLOps) and productionization of ML models. Familiarity with building data and metric generation pipelines, using tools like SQL or Spark, to answer business questions and assess system efficacy. Ability to communicate More ❯

in designing and implementing AI/ML solutions, including knowledge of common ML frameworks (e.g., TensorFlow, PyTorch), AI based cloud services in Azure and AWS, data science platforms, and MLOps tools. -Familiarity with various AI/ML techniques (e.g., supervised, unsupervised, reinforcement learning), natural language processing (NLP), computer vision, and generative AI models. -Solid understanding of different architecture domains (application More ❯

/entity relationships, NoSQL, JSON, XML, SQL and exposure to data visualisation tools (ETL/ELT). Data Science Tools: Proficiency in Numpy, Pandas, Matplotlib, Seaborn and Scikit-learn. MLOps: Experience building pipelines (CI/CD) using Bicep or similar technologies. Expertise in deploying, monitoring and managing machine learning models in production environments. API Development: An understanding of REST. Experience More ❯

Microsoft Azure AI services. Strong understanding of large language models, prompt engineering, and fine-tuning techniques. Experience with data manipulation libraries (e.g., Pandas, NumPy) and cloud platforms. Familiarity with MLOps, version control (e.g., Git), and deployment tools (e.g., Docker, Kubernetes). Excellent problem-solving skills and the ability to work on complex AI challenges. Nice to Have: Experience with NLP More ❯

scalable systems and high-volume, low latency, transaction/computation applications. Broad understanding of the software development lifecycle, including the application of LLM driven and Data Science DevOps/MLOps/AIOps methodologies. Expertise in data management and analytics, including data structures, data processing, data modelling, and statistical analysis. Knowledge of Python and C# for development and scripting. Leadership: Proven More ❯

scalable systems and high-volume, low latency, transaction/computation applications. Broad understanding of the software development lifecycle, including the application of LLM driven and Data Science DevOps/MLOps/AIOps methodologies. Expertise in data management and analytics, including data structures, data processing, data modelling, and statistical analysis. Knowledge of Python and C# for development and scripting. Leadership: Proven More ❯

scalable systems and high-volume, low latency, transaction/computation applications. Broad understanding of the software development lifecycle, including the application of LLM driven and Data Science DevOps/MLOps/AIOps methodologies. Expertise in data management and analytics, including data structures, data processing, data modelling, and statistical analysis. Knowledge of Python and C# for development and scripting. Leadership: Proven More ❯

scalable systems and high-volume, low latency, transaction/computation applications. Broad understanding of the software development lifecycle, including the application of LLM driven and Data Science DevOps/MLOps/AIOps methodologies. Expertise in data management and analytics, including data structures, data processing, data modelling, and statistical analysis. Knowledge of Python and C# for development and scripting. Leadership: Proven More ❯

scalable systems and high-volume, low latency, transaction/computation applications. Broad understanding of the software development lifecycle, including the application of LLM driven and Data Science DevOps/MLOps/AIOps methodologies. Expertise in data management and analytics, including data structures, data processing, data modelling, and statistical analysis. Knowledge of Python and C# for development and scripting. Leadership: Proven 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 ❯

and manage their data with efficiency and ease. You will work closely with people from a wide variety of domains, as well as our Insights, Analytics Engineers, Data Scientists, MLOps, MarTech and other Data Engineering teams. You will help manage our growing data needs and support increasingly complex business problems by building and promoting self-service tools and data best More ❯

GCP), Kubernetes, and containerised systems. Strong technical skills in Python, Java/Go, TensorFlow, PyTorch, and data engineering. Proven ability to engage directly with CxO-level stakeholders. Experience in MLOps, AI governance, and large-scale deployment. Recognised professional certifications in AI or cloud technologies. If you have these skills and would like to find out more, please apply now. More ❯

GCP), Kubernetes, and containerised systems. Strong technical skills in Python, Java/Go, TensorFlow, PyTorch, and data engineering. Proven ability to engage directly with CxO-level stakeholders. Experience in MLOps, AI governance, and large-scale deployment. Recognised professional certifications in AI or cloud technologies. If you have these skills and would like to find out more, please apply now. More ❯

GCP), Kubernetes, and containerised systems. Strong technical skills in Python, Java/Go, TensorFlow, PyTorch, and data engineering. Proven ability to engage directly with CxO-level stakeholders. Experience in MLOps, AI governance, and large-scale deployment. Recognised professional certifications in AI or cloud technologies. If you have these skills and would like to find out more, please apply now. More ❯

GCP), Kubernetes, and containerised systems. Strong technical skills in Python, Java/Go, TensorFlow, PyTorch, and data engineering. Proven ability to engage directly with CxO-level stakeholders. Experience in MLOps, AI governance, and large-scale deployment. Recognised professional certifications in AI or cloud technologies. If you have these skills and would like to find out more, please apply now. More ❯

GCP), Kubernetes, and containerised systems. Strong technical skills in Python, Java/Go, TensorFlow, PyTorch, and data engineering. Proven ability to engage directly with CxO-level stakeholders. Experience in MLOps, AI governance, and large-scale deployment. Recognised professional certifications in AI or cloud technologies. If you have these skills and would like to find out more, please apply now. More ❯

teams and mentor junior practitioners Ability to communicate complex technical concepts clearly to non-technical audiences Bonus Points For Participation in Kaggle or other data science competitions Experience with MLOps practices (CI/CD, model monitoring, DevOps integration) Familiarity with advanced NLP frameworks such as spaCy or Transformers MSc or PhD in a numerate discipline Financial services or banking experience More ❯

Strong programming experience (preferably Python or R), with experience of building, testing and deploying machine learning models Experience delivering predictive or prescriptive models into production, with knowledge of current MLOps principles Skilled in creating impactful data visualisations and dashboards Working knowledge of cloud platforms such as GCP or AWS, with Google preferred About us In return for all your hard More ❯

Strong programming experience (preferably Python or R), with experience of building, testing and deploying machine learning models Experience delivering predictive or prescriptive models into production, with knowledge of current MLOps principles Skilled in creating impactful data visualisations and dashboards Working knowledge of cloud platforms such as GCP or AWS, with Google preferred In return for all your hard work, you More ❯

Strong programming experience (preferably Python or R), with experience of building, testing and deploying machine learning models Experience delivering predictive or prescriptive models into production, with knowledge of current MLOps principles Skilled in creating impactful data visualisations and dashboards Working knowledge of cloud platforms such as GCP or AWS, with Google preferred In return for all your hard work, you More ❯

Computer Science, Statistics, or a related field.) Certifications in cloud platforms or data science tools (e.g., IBM Data Science Professional Certificate) are advantageous. Experience with data engineering tools and MLOps practices is a plus. ABOUT BUSINESS UNIT IBM Consulting is IBM's consulting and global professional services business, with market leading capabilities in business and technology transformation. With deep expertise 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 ❯

experience in DevOps engineering Solid knowledge of cloud platforms, e.g. Azure/AWS/GCP (mandatory) Mastery of Docker architecture, containerization, and CI/CD tools Proven experience in MLOps practices, integrating machine learning models into scalable, secure production environments is a great plus Comfortable working with Bitbucket, Git, Confluence, and Jira Familiarity with platforms like Databricks is a strong More ❯

working in B2C, e-commerce, subscription, retail, or fintech industries is a strong advantage Nice to Have Experience with NLP for customer feedback or support ticket analysis Exposure to MLOps for model deployment and monitoring Familiarity with tools like Amplitude, Mixpanel, or Google Analytics Why Join Us? Shape data-driven strategy for how we understand and engage with our customers More ❯