126 to 150 of 1,149 MLOps Jobs in the UK

and deploy advanced machine learning and behavioural intelligence models. Lead the transition of prototypes into scalable, cloud-native production systems. Architect data pipelines and model-serving infrastructure (Docker, Kubernetes, MLOps). Work with large-scale time series and behavioural data from diverse sensors. Contribute to strategic technical decisions and mentor junior engineers. Collaborate with cross-functional teams to align AI … highly desirable. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, Scikit-learn. Experience deploying AI solutions using AWS, GCP, or Azure. Hands-on experience with MLOps, CI/CD, and model performance monitoring. Background in behavioural biometrics, human-computer interaction, or large-scale sensor/time-series data is a plus. Passion for human-centred AI More ❯

and deploy advanced machine learning and behavioural intelligence models. Lead the transition of prototypes into scalable, cloud-native production systems. Architect data pipelines and model-serving infrastructure (Docker, Kubernetes, MLOps). Work with large-scale time series and behavioural data from diverse sensors. Contribute to strategic technical decisions and mentor junior engineers. Collaborate cross-functionally with product, UX, and leadership … Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for ML, and model performance monitoring. A background in behavioural biometrics, human-computer interaction, or large-scale sensor/time-series data is a strong plus. A More ❯

and deploy advanced machine learning and behavioural intelligence models. Lead the transition of prototypes into scalable, cloud-native production systems. Architect data pipelines and model-serving infrastructure (Docker, Kubernetes, MLOps). Work with large-scale time series and behavioural data from diverse sensors. Contribute to strategic technical decisions and mentor junior engineers. Collaborate cross-functionally with product, UX, and leadership … Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for ML, and model performance monitoring. A background in behavioural biometrics, human-computer interaction, or large-scale sensor/time-series data is a strong plus. A More ❯

and deploy advanced machine learning and behavioural intelligence models. Lead the transition of prototypes into scalable, cloud-native production systems. Architect data pipelines and model-serving infrastructure (Docker, Kubernetes, MLOps). Work with large-scale time series and behavioural data from diverse sensors. Contribute to strategic technical decisions and mentor junior engineers. Collaborate cross-functionally with product, UX, and leadership … Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS, GCP, or Azure. Hands-on experience with MLOps, CI/CD for ML, and model performance monitoring. Background in behavioural biometrics, human-computer interaction, or large-scale sensor/time-series data is a strong plus. A passion More ❯

attribution, predicting customer propensity, segmenting customer groups based on behavioral data, and recommending products and/or content. Fine-tune Large Language Models to business-specific use cases. Deploy MLOps pipelines together with our ML engineers. Work closely with data engineers, fellow data scientists/AI engineers, and consultants to ensure seamless integration and deployment of AI solutions that create … Excellent communication and problem-solving skills. Available to start working in the UK. Nice to Have Experience with natural language processing (NLP) or computer vision (CV). Knowledge of MLOps and model deployment pipelines. Familiarity with AI ethics and responsible AI principles. Experience working with large datasets and distributed computing. Contributions to open-source AI projects. We Offer Benefits vary More ❯

R&D into emerging techniques (e.g., graph neural networks for inventory routing, GenAI for buyer personalisation). - Manage and mentor a Senior Data Scientist, fostering growth in model optimisation, MLOps, and stakeholder collaboration. - Coordinate with Data Engineering to ensure seamless data pipelines for model inputs (e.g., real-time inventory feeds, third-party economic data). 3. Cross-Functional Collaboration - Partner … 7+ years in Data Science, with 2+ years leading teams in B2B, automotive, fintech, or supply chain domains. - Expertise in production-grade ML (model deployment, A/B testing, MLOps) and tools like MLflow, Airflow, or Kubeflow. - Mastery of Python, SQL, and cloud platforms (AWS/Asure/GCP). - Proven track record solving business problems with ML (e.g., pricing More ❯

R&D into emerging techniques (e.g., graph neural networks for inventory routing, GenAI for buyer personalisation). - Manage and mentor a Senior Data Scientist, fostering growth in model optimisation, MLOps, and stakeholder collaboration. - Coordinate with Data Engineering to ensure seamless data pipelines for model inputs (e.g., real-time inventory feeds, third-party economic data). 3. Cross-Functional Collaboration - Partner … 7+ years in Data Science, with 2+ years leading teams in B2B, automotive, fintech, or supply chain domains. - Expertise in production-grade ML (model deployment, A/B testing, MLOps) and tools like MLflow, Airflow, or Kubeflow. - Mastery of Python, SQL, and cloud platforms (AWS/Asure/GCP). - Proven track record solving business problems with ML (e.g., pricing More ❯

advanced analytics techniques, machine learning approaches, and modern pricing tools. ML Engineering Integration: Partner with ML Engineering to elevate model sophistication, overseeing integration with Radar API and ensuring smooth MLOps deployment pipelines. Leadership & Mentoring: Support and mentor junior analysts, sharing knowledge and promoting best practices across the team. Who are you: We know we have high expectations, so please don … and deliver meaningful change end-to-end Excellent communication and stakeholder skills, with the ability to present technical insights clearly to non-technical audiences Nice-to-have Familiarity with MLOps and development best practice, including production-grade model design and deployment, version control (e.g. Git), code reviews, CI/CD pipelines, unit testing, and collaborative workflows such as Agile. Experience More ❯

to help meet user’s needs. Develop and enhance CI/CD flows, improving quality, accountability and standards across the product stack. Work directly on integrating key elements of MLOps workflow with causal AI capabilities, ensuring robustness, scalability, and efficiency. Collaborate with cross-functional teams including data science, software engineering, and product to align technical solutions with business objectives and … skills in using and managing Kubernetes clusters. Good knowledge of DevOps tools and technologies, such as Helm, Docker, Terraform and CI/CD pipelines (GitHub Actions). Knowledge of MLOps especially on cloud environments: Vertex, Sagemaker, Synapse, is a huge plus. Strong Knowledge of the software development lifecycle (code review, version control, tooling, testing, etc.). Understanding of the full More ❯

and software engineers. Drive model interpretability, scalability, and reproducibility in high-stakes biomedical applications. Drive technical decision-making around architecture, model development, and data integration. Champion best practices in MLOps, model validation, and responsible AI, especially in regulated biomedical environments. Lead initiatives focused on Generative AI and Agentic AI, developing AI agents that can reason, plan, and interact autonomously with … data, tools, and systems. Mentor other engineers and data scientists; foster best practices around MLOps, experimentation tracking, and continuous integration. Why you? Basic Qualifications & Skills: We are looking for professionals with these required skills to achieve our goals: PhD or Master's degree in computer science, Machine Learning, Statistics, Computational Biology, or a related quantitative field. Extensive experience in AI More ❯

on experience with cloud platforms (e.g., AWS, GCP, Azure) and deploying AI models in production environments. Solid understanding of data structures, algorithms, and software engineering best practices. Experience with MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes) is highly desirable. Excellent problem-solving, communication, and collaboration skills. #J-18808-Ljbffr More ❯

Points Additional skills that would be beneficial include: Experience in a startup environment Knowledge of Python frameworks (Django, Flask, FastAPI), Rust, and machine learning libraries Familiarity with Generative AI, MLOps, CI/CD, and cloud platforms (AWS/GCP/Azure) Expertise with container tools like Docker and Kubernetes Ready to take the next step in your engineering career? Apply More ❯

TensorFlow, PyTorch, pyMC, pgmpy, ...) Hands-on experience with one or more cloud computing platforms (Azure - preferred, AWS, GCP). Understanding of the whole ML lifecycle and experience with MLOps/DataOps. Experience with Probabilistic Graphical Modelling (Bayesian Networks, Markov Random Fields, Factor Graphs, ...) Strong problem-solving skills and attention to detail. Good communication skills, fluent English. If interested More ❯

to extract insights and communicate results effectively. Innovate new modelling and machine learning approaches to enhance existing processes and capabilities. Collaborate with cross-functional teams, including engineering, product management, MLOps, and leadership, to define problem statements, scope projects, and deliver analytics solutions. Mentor peers in data science and model development, promoting best practices. Remain abreast of the latest technologies and More ❯

to extract insights and communicate results effectively. Innovate new modelling and machine learning approaches to enhance existing processes and capabilities. Collaborate with cross-functional teams, including engineering, product management, MLOps, and leadership, to define problem statements, scope projects, and deliver analytics solutions. Mentor peers in data science and model development, promoting best practices. Remain abreast of the latest technologies and More ❯

60k per annum As a Machine Learning Engineer , you will be part of an MLOps team, working alongside data scientists, software engineers, and other stakeholders to bring machine learning models to life. You will be responsible for deploying, maintaining, and monitoring models in production, improving model performance, and refining the machine learning infrastructure to support business objectives. Your role will More ❯

and reproducibility. Preferred Skills: Experience with NLP (Natural Language Processing), computer vision, or reinforcement learning. Mathematics & Algorithms: Strong knowledge of linear algebra, probability, statistics, and optimization techniques. Knowledge of MLOps, CI/CD pipelines, and automated testing for machine learning models. Version Control: Familiarity with version control tools such as DevOps/Git. Soft Skills: Problem Solving: Strong analytical and More ❯

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 ❯

have 5+ years of experience in technical product management Experience working with developerteams and productionizing AI or other data-intensive applications Breadth of knowledge or familiarity with GenAI platforms, MLOps platforms, AI toolkits Deep understanding of software development best practices Organizational and communication skills to effectively coordinate and work with engineers, UX, subject matter experts, other product managers, and senior More ❯

pipelines. Familiarity with data lake architectures and tools like Delta Lake , LakeFS , or Databricks . Knowledge of security and compliance best practices (e.g., SOC2, ISO 27001). Exposure to MLOps platforms or frameworks (e.g., MLflow, Kubeflow, Vertex AI). What We Offer Competitive salary + equity Flexible work environment and remote-friendly culture Opportunities to work on cutting-edge AI More ❯

pipelines. Familiarity with data lake architectures and tools like Delta Lake , LakeFS , or Databricks . Knowledge of security and compliance best practices (e.g., SOC2, ISO 27001). Exposure to MLOps platforms or frameworks (e.g., MLflow, Kubeflow, Vertex AI). What We Offer Competitive salary + equity Flexible work environment and remote-friendly culture Opportunities to work on cutting-edge AI More ❯

pipelines. Familiarity with data lake architectures and tools like Delta Lake , LakeFS , or Databricks . Knowledge of security and compliance best practices (e.g., SOC2, ISO 27001). Exposure to MLOps platforms or frameworks (e.g., MLflow, Kubeflow, Vertex AI). What We Offer Competitive salary + equity Flexible work environment and remote-friendly culture Opportunities to work on cutting-edge AI More ❯

pipelines. Familiarity with data lake architectures and tools like Delta Lake , LakeFS , or Databricks . Knowledge of security and compliance best practices (e.g., SOC2, ISO 27001). Exposure to MLOps platforms or frameworks (e.g., MLflow, Kubeflow, Vertex AI). What We Offer Competitive salary + equity Flexible work environment and remote-friendly culture Opportunities to work on cutting-edge AI More ❯

pipelines. Familiarity with data lake architectures and tools like Delta Lake , LakeFS , or Databricks . Knowledge of security and compliance best practices (e.g., SOC2, ISO 27001). Exposure to MLOps platforms or frameworks (e.g., MLflow, Kubeflow, Vertex AI). What We Offer Competitive salary + equity Flexible work environment and remote-friendly culture Opportunities to work on cutting-edge AI More ❯

pipelines. Familiarity with data lake architectures and tools like Delta Lake , LakeFS , or Databricks . Knowledge of security and compliance best practices (e.g., SOC2, ISO 27001). Exposure to MLOps platforms or frameworks (e.g., MLflow, Kubeflow, Vertex AI). What We Offer Competitive salary + equity Flexible work environment and remote-friendly culture Opportunities to work on cutting-edge AI More ❯