1 to 25 of 137 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 ...

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 ...

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 ...

solutions based on real user feedback and real-world constraints. Learn modern tooling and practices Gain hands-on experience with ML frameworks, cloud infrastructure, MLOps tools, and best practices for building scalable AI systems. Communicate clearly Translate technical findings into clear, structured insights for collaborators across technical and business teams. ...

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 ...

Spark. • Ethics: Knowledge of AI ethics and governance. • Methodologies: Agile and Scrum project management. Desired Skills & Experience • Deep knowledge of machine learning operations (MLOps) and experience in deploying, monitoring, and maintaining AI models in production environments. • Proficiency in data engineering for AI, including data preprocessing, feature engineering, and pipeline creation. ...

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 ...

Azure) and containerisation (Docker, Kubernetes) Solid understanding of ML fundamentals (model training, evaluation, common architectures) Desired Skills (Bonus Points) Experience with MLOps tooling (MLflow, Kubeflow, Weights & Biases, or similar) Building data pipelines (real-time or batch) using tools like Apache Spark, Kafka, Airflow, or dbt Familiarity with recommender systems, transformers ...

TypeScript/JavaScript helpful for front-end integrations. AI & data: LLMs (OpenAI/Anthropic-style APIs), vector databases/RAG, agent frameworks, basic MLOps for deploying and monitoring AI systems in production. Orchestration: Workflow engines, event-driven architectures, multi-agent coordination systems. Cloud & infra: Azure or AWS, containerised services (Docker ...

validation. Implement feature engineering and data augmentation techniques. Integration & Deployment Develop APIs or services to integrate ML models into production systems. Work with MLOps tools for model deployment, versioning, and monitoring. Performance Optimization Evaluate models using metrics like accuracy, precision, recall, F1-score. Optimize models for scalability, latency, and resource ...

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 ...

your skills in a fast-moving AI environment. Nice to Have (But Not Essential) Experience with vector databases , embeddings, or prompt optimisation. Exposure to MLOps , model deployment, or monitoring tools. Background in data engineering, front-end development, or UX-aware AI applications . Interest or experience in healthcare or regulated ...

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 ...

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 ...