301 to 325 of 1,206 MLOps Jobs in the UK

client requirements into scalable, cloud-based AI architectures that address both technical feasibility and business impact. Propose end-to-end AI/ML solutions—including model design, data pipelines, MLOps, and platform integration—tailored to each opportunity. Support Sales and Bid Activity Lead the technical response for AI-related RFPs, RFIs, and proposals, including solution overviews, technical narratives, architecture diagrams … them with AI/ML solutions in cloud environments (Azure, AWS, or GCP). Deep technical understanding of AI/ML concepts: supervised and unsupervised learning, GenAI, LLMs, embeddings, MLOps, vector search. Experience designing solutions using tools such as Azure ML, AWS SageMaker, Google Vertex AI, Databricks, LangChain, and Hugging Face. Ability to develop architecture artefacts (e.g., HLDs), estimate effort 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 ❯

skills. Desirable: Databricks certifications (e.g., Data Engineer Associate/Professional or Solutions Architect). Familiarity with MLflow, dbt, and BI tools such as Power BI or Tableau. Exposure to MLOps practices and deploying ML models within Databricks. Experience working within Agile and DevOps-driven delivery environments. More ❯

using LangGraph, AutoGen, CrewAI, or custom frameworks • Integrate AI agents with enterprise tools (ServiceNow, Jira, SAP, Slack, etc.) • Optimize model performance (quantization, distillation, batching, caching) • Collaborate with DevOps and MLOps teams to build CI/CD pipelines for models and agents • Conduct code and research reviews, mentor junior engineers, and contribute to technical strategy • 5–8 years of hands-on More ❯

Machine Learning, Cloud, DevOps & Software Good theoretical understanding of machine learning, neural networks, and other computer vision topics Hands-on experience with Python and PyTorch Hands-on experience with MLOps frameworks and platforms (We use ClearML!) Experience with additional programming languages and frameworks is a plus Experience working with cloud platforms (GCP, AWS, Azure) Experience using Generative AI tools such More ❯

leveraging cloud-native tools and services. AI Feature Integration Collaborate with engineering and product teams to embed AI-driven functionality into user-facing software. Technical Leadership Set standards for MLOps, automation, and performance tuning across the engineering team. Generative AI & LLMs Explore and integrate modern techniques such as large language models and generative architectures. Mentorship & Collaboration Support peers through code More ❯

leveraging cloud-native tools and services. AI Feature Integration Collaborate with engineering and product teams to embed AI-driven functionality into user-facing software. Technical Leadership Set standards for MLOps, automation, and performance tuning across the engineering team. Generative AI & LLMs Explore and integrate modern techniques such as large language models and generative architectures. Mentorship & Collaboration Support peers through code More ❯

leveraging cloud-native tools and services. AI Feature Integration Collaborate with engineering and product teams to embed AI-driven functionality into user-facing software. Technical Leadership Set standards for MLOps, automation, and performance tuning across the engineering team. Generative AI & LLMs Explore and integrate modern techniques such as large language models and generative architectures. Mentorship & Collaboration Support peers through code More ❯

Python libraries: scikit-learn, TensorFlow, PyTorch, Huggingface Transformers Proficiency in working with cloud environments: AWS, Azure, or GCP Nice To Have Front-end development experience using React.js Familiarity with MLOps tools: MLflow, Kubeflow, Airflow Knowledge of self-supervised or contrastive learning methods: SimCLR, CLIP What We Offer Work on cutting-edge AI/ML technologies and architectures. Collaborate in a More ❯

solving skills. Databricks certifications (e.g., Data Engineer Associate/Professional or Solutions Architect). Familiarity with MLflow, dbt, and BI tools such as Power BI or Tableau. Exposure to MLOps practices and deploying ML models within Databricks. Experience working within Agile and DevOps-driven delivery environments. Seniority level Seniority level Not Applicable Employment type Employment type Full-time Job function More ❯

Python and object-oriented paradigm. Agile software development experience. Preferred Qualifications Experience in Biomedical data or computational sciences. Experience in cloud platforms such as GCP or AWS. Experience with MLOps/LLMOps frameworks and best practices. Benefits Competitive compensation package. Private medical insurance. Life insurance (4 x salary). Personal development budget. Individual wellbeing budget. 25 days holiday plus bank More ❯

Trainer/Instructor/Lecturer/Teacher Consultant/Coach/Mentor/Educator ) Ability to explain complex topics clearly and adapt to different learning levels. Familiarity with modern MLOps practices, reproducibility, and collaborative workflows. Practical experience deploying or training models in cloud environments (AWS, GCP or Azure) This is a fully remote working position & salary is £65,000, with More ❯

and frameworks to enhance the 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. Essential skills/knowledge/experience: Solid experience as a Security Architect, with a focus More ❯

engineering, prompt tuning, and evaluation of generative model outputs. Experience working with healthcare or sensitive data (HIPAA/GDPR compliance awareness). Strong problem-solving skills. Bonus: Experience with MLOps, Kubernetes, AWS/GCP, and deploying models in production. Robert Walters Operations Limited is an employment business and employment agency and welcomes applications from all candidates About the job Contract More ❯

train very large AI models. Build and maintain efficient, scalable, and reliable AI infrastructure, tools, and pipelines to support the deployment of machine learning models in collaboration with the MLOps team. Continuously research and stay current with the latest advancements in AI, machine learning, and data science. Contribute to the growth of the AI team by sharing knowledge, providing mentorship More ❯

office (3 days/week). Preferred Qualifications Prior work in regulated healthcare or finance environments; familiarity with HIPAA, NHS DSPT, GDPR . Experience orchestrating GPU/AI workloads , MLops, or large‐language‐model serving. Knowledge of edge/IoT deployments and over‐the‐air update strategies. Exposure to observability stacks (OpenTelemetry, Loki) and security tooling (Falco, Aqua, Wiz). More ❯

business-critical machine learning models using Azure ML in production environments. Strong skills in data wrangling using Python, SQL, and ADF . Proficiency in CI/CD, DevOps/MLOps , and version control systems. Familiarity with data visualization and reporting tools, ideally PowerBI. Excellent communication and interpersonal skills, with the ability to convey technical concepts to non-technical stakeholders. Experience More ❯

Demonstrated ability to build relationships with stakeholders and subject matter experts. Familiarity with high compute cloud-based platforms and services, in particular AWS. Familiarity with code version control and MLOps deployment approaches. Ability to understand healthcare challenges and adapt accordingly the AI solutions. Cross-functions high adaptability to meet cross organization goals. Required/Preferred Education Advanced degree (MS or More ❯

like Apache Airflow, Spark, or 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 mindset and ability to work More ❯

like Apache Airflow, Spark, or 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 mindset and ability to work More ❯

Docker and Kubernetes. Knowledge of multi-cloud or hybrid cloud environments. Microsoft Azure certifications (e.g., Azure Solutions Architect Expert, Azure DevOps Engineer Expert). Familiarity with data engineering or MLOps practices. Exposure to Agile working methodologies and experience in fast-paced environments. Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience). Interested? If you More ❯

Machine Learning, Cloud, DevOps & Software Good theoretical understanding of machine learning, neural networks, and other computer vision topics Hands-on experience with Python and PyTorch Hands-on experience with MLOps frameworks and platforms (We use ClearML!) Experience with additional programming languages and frameworks is a plus Experience working with cloud platforms (GCP, AWS, Azure) Experience using Generative AI tools such More ❯

SVM, tree-based methods, and NLP. Expertise in generative AI tools: Experience with prompt-engineering, fine-tuning language models, and selecting the right models for various tasks. Proficiency in MLOps: Knowledge of building production applications in cloud architecture (Azure, AWS, or similar), and understanding of best practices for the full software development life cycle. Strong programming skills: Proficient in Python More ❯

Exceptional communication skills, both written and verbal – able to translate complex technical subject matter into easily understood presentations and written documentation for mixed technical audiences. Desirable: MLFlow and other MLOps/Machine Learning Engineering processes to support advanced analytical use cases Data modelling including Kimball Container technologies such as Kubernetes and Docker Experience translating designs of Azure data solutions into More ❯

Exceptional communication skills, both written and verbal – able to translate complex technical subject matter into easily understood presentations and written documentation for mixed technical audiences. Desirable: MLFlow and other MLOps/Machine Learning Engineering processes to support advanced analytical use cases Data modelling including Kimball Container technologies such as Kubernetes and Docker Experience translating designs of Azure data solutions into More ❯