326 to 350 of 1,027 MLOps Jobs in England

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. Support peers through code reviews, design 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. Support peers through code reviews, design 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. Support peers through code reviews, design More ❯

pricing and desirability scoring, ensuring ethical, bias-free automation. Cross-Functional Leadership Lead a team of Product Managers (Data, Salesforce, Decision Engine) and collaborate with: Data Science & Engineering: Scale MLOps, model governance, data quality. Commercial Teams: Develop pricing models for data-as-a-service (DaaS). Legal & Compliance: Embed GDPR, PSD2, and AI ethics into product design. Drive revenue through 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 ❯

image processing , or graph models . Experience applying probabilistic models in real-world applications (e.g., recommendation systems, anomaly detection, personalized healthcare, etc.). Understanding of modern ML pipelines and MLOps (e.g., MLFlow, Weights & Biases). Experience with recent trends such as foundation models , causal inference , or RL with uncertainty . Track record of publishing or presenting work (e.g., NeurIPS, ICML More ❯

DevOps tooling such Terraform, Packer, Ansible, Chef, Gitlab Experience with containerization technologies and orchestration tools Familiarity with data preprocessing and feature engineering techniques for ML model training. Familiarity with MLOps tooling Benefits Be part of a creative, world-leading team Competitive salary and share options scheme Contributory pension scheme Private Medical Insurance Life Assurance Cycle-to-work Scheme Flexible working More ❯

new tools and technologies. Preferred Qualifications: AWS certifications (e.g., Solutions Architect Associate/Professional, DevOps Engineer). Experience deploying and maintaining data processing and machine learning workloads. Familiarity with MLOps tools (e.g., MLflow, Airflow, BentoML). Knowledge of distributed systems, caching strategies, content delivery networks (CDNs), and load balancing. Understanding of Zero Trust Network (ZTN) concepts using Cloudflare. Basic experience 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 ❯

models Experience with Computer Vision models and frameworks, including CNNs and GANs, particularly for image data use cases Experience working in B2B or consulting environments Familiarity with DevOps or MLOps practices Why Join Firemind Work on real AI solutions with practical impact Flexible hybrid or remote work with hubs in the UK and Finland Collaborate with experienced engineers in a 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 ❯

Azure/GCP/AWS). Skills we'd also like to hear about: Evidence of modelling experience applied to industry relevant use cases. Familiarity with working in an MLOps environment. Familiarity with simulation techniques. Familiarity with optimisation techniques. What you'll receive from us: No matter where you may be in your career or personal life, our benefits are More ❯

Azure/GCP/AWS). Skills we'd also like to hear about: Evidence of modelling experience applied to industry relevant use cases. Familiarity with working in an MLOps environment. Familiarity with simulation techniques. Familiarity with optimisation techniques. What you'll receive from us: No matter where you may be in your career or personal life, our benefits are More ❯

Azure/GCP/AWS). Skills we'd also like to hear about: Evidence of modelling experience applied to industry relevant use cases. Familiarity with working in an MLOps environment. Familiarity with simulation techniques. Familiarity with optimisation techniques. What you'll receive from us: No matter where you may be in your career or personal life, our benefits are More ❯

Azure/GCP/AWS). Skills we'd also like to hear about: Evidence of modelling experience applied to industry relevant use cases. Familiarity with working in an MLOps environment. Familiarity with simulation techniques. Familiarity with optimisation techniques. What you'll receive from us: No matter where you may be in your career or personal life, our benefits are More ❯

language model training Collaborate with researchers to implement novel data processing pipelines Develop an easy-to-use, secure, and robust developer experience for researchers and engineers Contribute to the MLOps best practices at Lila Sciences and write technical documentation for staff Qualifications: 3+ years of experience in software engineering, with a focus in data engineering or DevOps Demonstrated experience deploying More ❯

managing business-critical machine learning models using Azure ML in Production environments. Experience in data wrangling using Python, SQL and ADF. Experience in CI/CD and DevOps/MLOps and version control. Familiarity with data visualization and reporting tools, ideally PowerBI. Good written and verbal communication and interpersonal skills. Ability to convey technical concepts to non-technical stakeholders. Experience More ❯

managing business-critical machine learning models using Azure ML in Production environments. Experience in data wrangling using Python, SQL and ADF. Experience in CI/CD and DevOps/MLOps and version control. Familiarity with data visualization and reporting tools, ideally PowerBI. Good written and verbal communication and interpersonal skills. Ability to convey technical concepts to non-technical stakeholders. Experience More ❯

Pandas, Spark, SQL). Experience with version control (Git). Cloud experience (Azure, GCP, AWS). Additional desirable skills include: Modeling experience in industry-relevant use cases. Familiarity with MLOps environments. Experience with simulation and optimization techniques. What you'll receive from us: We offer benefits designed to support and recognize your contributions, including flexible working arrangements, private medical cover More ❯

managing business-critical machine learning models using Azure ML in Production environments. Experience in data wrangling using Python, SQL and ADF. Experience in CI/CD and DevOps/MLOps and version control. Familiarity with data visualization and reporting tools, ideally PowerBI. Good written and verbal communication and interpersonal skills. Ability to convey technical concepts to non-technical stakeholders. Experience More ❯

strong sense of ownership. A numerate degree (e.g. Maths, Stats, Engineering, Computer Science). Desirable: Experience using Databricks or working in a cloud-based environment like Azure. Exposure to MLOps, version control, or productionising models. Experience working with Jira and Confluence in an Agile environment is advantageous. Streamlit, Power BI or other standard BI software experience Experience from outside the More ❯

learning and delivering them from prototype through to production Strong understanding of machine learning applications, development life cycle processes and tools: CI/CD, version control (git), testing frameworks, MLOps Comfortable working with Docker and containerised applications Experience with data science Python libraries such as Scikit-learn, Pandas, NumPy, Pytorch etc. Experience using AWS or similar cloud computing platform Great More ❯

strong sense of ownership. A numerate degree (e.g. Maths, Stats, Engineering, Computer Science). Desirable: Experience using Databricks or working in a cloud-based environment like Azure. Exposure to MLOps, version control, or productionising models. Experience working with Jira and Confluence in an Agile environment is advantageous. Streamlit, Power BI or other standard BI software experience Experience from outside the More ❯

AWS, Azure, or Google Cloud for AI model deployment. Data Visualisation: Ability to present insights effectively using tools like Matplotlib, Seaborn, Tableau, or Power BI. Model Deployment: Understanding of MLOps principles, APIs, and containerization (Docker, Kubernetes) for productionizing AI models. Business-Focused AI Application: Ability to translate AI solutions into measurable business impact. Why Wowcher is your Next Stop: Our More ❯