1 to 25 of 215 MLOps Jobs in the UK excluding London

with AI/ML workflows or deploying machine learning models in production. Knowledge of big data technologies like Hadoop, Hive, or Spark. Familiarity with MLOps tools and practices, such as MLflow, Kubeflow, or DataRobot. Education: Bachelor's degree in Computer Science, Software Engineering, or related field (or equivalent practical experience More ❯

of 5years. Strong programming skills in Python and preferably SQL, javascript. Experience with Agentic AI. Familiarity with cloud platforms (AWS, Azure, Google Cloud) and MLOps tools. Understanding of data structures, algorithms, and software engineering principles and also when to prototype. Experience with data preprocessing, feature engineering, and model evaluation techniques. More ❯

Mathematics, or a technical field. Proficiency in Python (or R), with hands-on experience in ML and statistical modeling. End-to-end experience with MLOps , from experimentation to deployment and monitoring. Strong grasp of ethical AI practices: model explainability, transparency, bias mitigation. Hands-on with AWS services (SageMaker, Glue, Redshift More ❯

our platform. Ensure smooth end-to-end integration of AI/ML functionality within broader product development efforts. Technical Leadership Define best practices for MLOps, model deployment, and performance tuning. Evaluate and implement new frameworks, tools, and cloud-native AI solutions (including LLMs). Make strategic technical decisions that align More ❯

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 More ❯

techniques. Proficient in version control, CI/CD pipelines, and test-driven development. Nice to Have: Experience within financial services or fintech. Familiarity with MLOps tools (e.g., MLflow, Kubeflow, SageMaker). Understanding of regulatory or compliance frameworks. Academic background in mathematics, statistics, or quantitative disciplines. Who You Are: A natural More ❯

and maintaining real-time data pipelines. Experience with ETL processes, Python, and SQL. Familiarity with big data technologies like Apache Hadoop and Apache Spark. MLOps & Deployment: Experience deploying and maintaining ML inference pipelines. Proficiency with Docker and Kubernetes. Familiarity with AWS cloud platform. The Perfect Candidate Also Has : Programming Languages More ❯

ability to engage senior stakeholders Nice to Have: Experience in consulting or client-facing delivery roles Knowledge of cloud platforms (AWS, GCP, Azure) and MLOps best practices Advanced degree (MSc or PhD) in a quantitative discipline Why Join Us? High-impact work with world-class clients Competitive salary and bonus More ❯

other relevant programming languages. Experience with ML frameworks like TensorFlow, PyTorch, and Scikit-learn. Hands-on experience with Microsoft Azure AI services. Knowledge of MLOps best practices. Experience with Azure data and analytics services such as Data Factory, Data Lake, and Synapse. Experience designing AI solutions, including virtual assistants and More ❯

CI/CD for microservices or ML pipelines. Solid understanding of networking, Linux, and security fundamentals. Preferred Qualifications Experience supporting GPU‑accelerated workloads or MLOps/LLMOps platforms. Familiarity with service mesh (Istio, Linkerd) and event‑driven architectures (Kafka, Pub/Sub). Knowledge of distributed storage systems (Ceph, MinIO More ❯

agile working environment, with a focus on iterative and collaborative project delivery. Have worked with data visualisation tools e.g. Tableau. Experience in model monitoring. (MLOPS experience would be desirable.) Have gained a master's in a quantitative field such as Computer Science, Statistics or related disciplines. Recruitment Process: Pre-screen More ❯

PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. 📩 Interested? Apply below or email me at mmatysik@trg-uk.com. More ❯

sources, 3rd party providers and publicly available data. Technology & Infrastructure Advisory: Assess and recommend data science tooling, platform architecture (cloud/on‑premise), and MLOps practices to ensure scalable, maintainable analytics pipelines (including API calls to various services) What You’ll Bring: Extensive experience in data strategy and analytics consulting More ❯

and reinforcement learning. Experience with cloud-based AI deployment (AWS, GCP, or Azure). Proficiency in Python, TypeScript, or Go. Solid grasp of DevOps, MLOps, and scalable AI infrastructure. Excellent stakeholder management and communication skills. Ability to work cross-functionally with product managers, engineers, and business leaders. Experience leading and More ❯

. 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 More ❯

. 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 More ❯

. 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 More ❯

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 More ❯

are well on our way-but there's still an exciting journey ahead. Join us at the heart of trust. As part of the MLOps team, you'll work closely with data scientists, software engineers, and other stakeholders to bring machine learning models to life-ensuring they're deployed, maintained More ❯

Python/other AI-related languages. Strong SQL and data analytics skills. Familiarity with cloud platforms (AWS and Azure) for AI deployment. Knowledge of MLOps principles for scaling AI models. Understanding of knowledge graphs, semantic search, and vector databases. AI Ethics and Responsible AI Awareness of AI ethics, bias mitigation More ❯

Scala, C# or Java, cloud SDKs and APIs. AI/ML expertise for pipeline efficiency, familiar with TensorFlow, PyTorch, AutoML, Python/R, and MLOps (MLflow, Kubeflow). Solid in DevOps, CI/CD automation with Bitbucket Pipelines, Azure DevOps, GitHub. Automate deployment of data pipelines and applications using Bash More ❯

Qualifications: Strong experience in AI/ML development focusing on LLMs and biomedical NLP. Proficiency in deep learning frameworks (TensorFlow, PyTorch). Experience with MLOps tools and cloud environments (AWS, Azure, GCP). Expertise in model inference optimization techniques. Understanding of biomedical ontologies and healthcare data formats. Experience deploying AI More ❯

Strong proficiency in Python and SQL. Hands-on experience with Power BI or similar data visualisation tools. familiarity with version control (e.g., Git) and MLOps principles. Great communication skills both verbally and written. The role is offering a salary of up to £50,000 per annum and comes with a More ❯

sensitive data (HIPAA/GDPR compliance awareness). Strong problem-solving skills and ability to move fast in a startup environment. Bonus: Experience with MLOps, Kubernetes, AWS/GCP, and deploying models in production. Work Permit UK work permit required More ❯

enterprise integration. Expertise in LLMs, NLP/NLU, Conversational/GenAI, AI Search, and Virtual Agents. Proficiency in programming & AI development (Python, OpenAI APIs, MLOps frameworks). Nice-to-Haves: Experience with multilingual AI models for global translation. AI certifications (e.g., Azure AI Engineer, Google ML Engineer, TOGAF). What More ❯