1 to 25 of 129 MLOps Jobs in the UK

Strong knowledge of Machine Learning algorithms and statistics. Experience with SQL/NoSQL databases and big data tools (Spark, Hadoop preferred). Experience with MLOps tools such as Docker, Kubernetes, CI/CD pipelines. Preferred Skills:- Experience with LLMs/Generative AI (OpenAI, Hugging Face, LangChain). Cloud experience ...

control. Strong communication skills, especially with non-technical customers. Desirable (SEO-Optimised) Experience with cloud platforms (AWS, Azure, GCP). Docker/Kubernetes & modern MLOps tooling. Experience across NLP, tabular modelling or computer vision. Exposure to LangChain, vector databases or AI-augmented development workflows. Benefits 35 days leave, including public ...

with call/contact-centre analytics, Microsoft Teams Graph API, or telephony platforms (BroadWorks, Webex Calling). Knowledge of data governance, model ethics, and MLOps practices. Exposure to data visualization and predictive analytics for customer-experience metrics. Advanced degree in AI, ML, Data Science, or related discipline. ISTQB AI Testing ...

enterprise. Work with a multi-functional team (DevOps, data engineers, developers, testers, Infosec) to productionize AI services on AWS. Enhance our tech stack, including MLOps, CI/CD pipelines, UI, and AI Python libraries. Develop prompts, fine-tune models, and track results. Evaluate third-party GenAI and LLM technologies ...

technical challenges Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related technical discipline Bonus Skills/Experience Understanding of MLOps, model serving, scaling and monitoring workflows (e.g., BentoML, MLflow, Vertex AI, AWS Sagemaker) Experience building streaming + batch data ingestion and transformation pipelines (Spark/ ...

serving, versioning, and lifecycle management Lead documentation, knowledge transfer, and mentoring to upskill internal teams Technical requirements Strong Python and ML frameworks (PyTorch, TensorFlow) MLOps tooling (MLflow, Kubeflow or similar) Databricks Docker, Kubernetes, CI/CD pipelines Cloud platforms (AWS, Azure or GCP); Terraform experience preferred Financial services experience highly ...

Take validated prototypes from our Data Science team and re-engineer them into high-performance, maintainable codebases that integrate seamlessly with client ecosystems. Infrastructure & MLOps: Build and maintain CI/CD pipelines specifically for machine learning, ensuring that deployments are predictable, reproducible, and secure. Performance Optimization: Profile and optimize model ...

integrations that embed AI into customer journeys, internal tools, and digital platforms* Own model lifecycle processes including deployment, monitoring, evaluation, and retraining* Implement robust MLOps practices to ensure reliability, performance, and scalability* Mentor engineers and contribute to shared tooling, reusable patterns, and engineering standards Required Experience* Strong software engineering background ...

every model we build is fair, free from bias, and explainable to consumers, customers, and regulators. Engineering & Deployment: Work within the engineering team on MLOps to containerise, deploy, and monitor models in high-scale production. Skills & Requirements Core Data Science: Foundational Stats: You must have an excellent grasp of Linear ...

ready ML models. Prepare, transform, and validate complex datasets to ensure high-quality inputs for your models. Utilize cloud platforms (AWS, Azure, GCP) and MLOps practices for seamless deployment and monitoring of ML solutions. Write modular, production-grade code using Python and maintain version control with Git. What ...

closely related field. Nice to Have Skills * Experience with Databricks for data engineering or ML workflows. * Familiarity with Azure ML, MLflow, or similar MLOps tooling. * Exposure to feature engineering best practices and model lifecycle management. Soft Skills * Strong communication skills with the ability to explain complex concepts simply. * Comfortable ...

services. Apply data modelling concepts (e.g., medallion architecture) and ensure data quality and governance. Collaborate with DevOps teams to automate CI/CD and MLOps processes using Azure DevOps, Kubernetes, and Terraform. Visualize and communicate insights using Power BI, Tableau, and PowerApps. Mentor junior engineers and contribute to internal knowledge ...

Design and implement Onsera's agentic AI platform – architect LLM/agent framework selection, standardized patterns for tools, memory, guardrails, evaluation, and observability Define MLOps protocols for agentic systems – environment separation, versioning of prompts, tools, and policies, cost controls, rate-limiting, and fail-safe mechanisms Bridge data science and platform ...

. AI & NLP - Practical experience in Artificial Intelligence and Natural Language Processing (NLP) . Cloud Platforms - Hands-on experience with AWS or Azure environments. MLOps & Deployment Experience in: - Model deployment and productionization - Model governance and lifecycle management - Version control tools such as Git - CI/CD pipelines for ML workflows ...

TensorFlow, PyTorch, or scikit-learn Eagerness to learn, curiosity, and a problem-solving mindset Nice to Have Cloud experience (AWS, GCP, Azure) Familiarity with MLOps tools (Docker, MLflow, Kubeflow) Deep learning knowledge (CNNs, RNNs, Transformers) Internship, research, or academic projects in ML/AI Why Join Hands-on experience with ...

Data Science/ML roles Strong data science foundations (EDA, feature engineering, model evaluation, validation) Hands-on experience with ML models in production Cloud & MLOps exposure (GCP preferred; AWS/Azure acceptable) Experience with GenAI/LLMs (commercial or serious hands-on experimentation) Strong Python and modern ML tooling (e.g. ...

Mathematics Computer Science or a related quantitative discipline Desirable Skills for the Data Scientist: Experience with deep learning frameworks advanced modelling techniques Familiarity with MLOps concepts model monitoring deployment pipelines Exposure to tools such as Databricks MLflow feature stores Experience working in Agile product-led delivery environments Understanding of data ...

Microsoft AI Foundry or Ollama advantageous). Strong grasp of CI/CD, testing, version control, secure coding, and modern engineering workflows. Exposure to MLOps tools such as MLflow, Kubeflow, or Azure ML. ...

scipy, scikit-learn, TensorFlow or PyTorch. Experience working across cloud environments (GCP, AWS, or Azure) and analytics platforms such as Dataiku. Good understanding of MLOps practices, including deployment, monitoring, and retraining pipelines. Proven ability to work cross-functionally with marketing, CRM, product, and engineering teams. Excellent communication, leadership, and stakeholder ...

analytical, data science and AI projects. - Build, maintain and optimise data pipelines, analytical models and data architecture. - Develop and operationalise machine learning solutions, applying MLOps best practice. - Produce high-quality, accessible dashboards and tools using platforms such as Power BI. - Work closely with senior leaders to shape strategic insight, policy ...

production environments Strong Python skills Deep knowledge of ML algorithms, statistics, and data modelling Hands-on experience with TensorFlow, PyTorch, or Keras Cloud & MLOps experience (AWS, Azure, or GCP) NLP or recent LLM experience highly relevant Comfortable operating at Staff IC level Package Up to £100k base (flexible for exceptional ...

multi-supplier environment. Familiarity with data science tooling and terminology (Python, SQL, etc.) is desirable. Understanding of cloud platforms (Azure, AWS, GCP) and MLOps and DevOps practices. Demonstrable experience working as a Business Analyst in large complex organisations, preferably within a consultancy. Benefits: Hybrid working model allowing flexibility. Opportunity ...

explain clearly to non-technical audiences DS background that has moved into AI engineering/LLM product delivery is ideal Bonus: Databricks, Azure, MLOps/CI-CD experience Interested? Please apply below. ...

solid understanding of machine learning fundamentals and data workflows 💬 Strong communication skills and a collaborative mindset ⭐ Big bonus points for: ⚙️ Exposure to ML pipelines, MLOps, or production ML systems 📦 Experience with tools such as Databricks, Snowflake, or similar platforms 🔍 Familiarity with version control, testing practices, or CI/CD workflows ...

internal stakeholders Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment Experience of appropriate version control and environment management (such as venvs or Docker) Experience of writing technical project proposals ...