1 to 25 of 58 MLOps Jobs in the UK excluding London

tuning, and evaluation. Hands-on experience with core GenAI frameworks (e.g., LangChain, LlamaIndex) and Agentic AI frameworks (e.g., AutoGen, CrewAI, LangGraph). Proficiency in MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes). Strong working knowledge and practical deployment experience on major cloud platforms (AWS, Azure, GCP), including their ...

LlamaIndex and agent frameworks like AutoGen, CrewAI or LangGraph . Experience building RAG architectures with vector databases (Pinecone, Weaviate, FAISS). Strong understanding of MLOps/LLMOps (MLflow, Kubeflow, Docker, Kubernetes). Experience deploying AI solutions on AWS, Azure or GCP . Solid software engineering and full-stack development experience ...

engineering, model tuning, and AI evaluation methodologies . Experience building production-grade AI systems using Python and ML frameworks (PyTorch, TensorFlow). Knowledge of MLOps/LLMOps practices and tooling (MLflow, Kubeflow, Docker, Kubernetes). Experience delivering AI solutions on AWS, Azure or GCP Experience leading or mentoring teams ...

TensorFlow, PyTorch, or Scikit-learn • Experience working with SQL and large datasets • Familiarity with data pipelines, feature engineering, and model optimisation • Understanding of MLOps practices, model deployment, and monitoring • Experience working with cloud platforms such as AWS, GCP, or Azure • Strong analytical thinking and problem-solving skills Experience Required ...

skills. Preferred Qualifications: Experience designing AI and advanced analytics on Foundry or similar big data platforms for pharma/commercial data applications. Knowledge of MLOps, DevOps, CI/CD, and automated model pipelines within Foundry and cloud-based environments. Familiarity with big data ecosystems (Foundry, Spark, Hadoop) and commercial data ...

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 ...

self-start when necessary. • Flexibility, we pride ourselves on doing what is necessary to make the whole organisation successful. Bonus Points: • Knowledge of MLOps principles and best practices. • Experience with distributed computing and large-scale data processing. How to apply? Please send a CV to danni@cortechtalentsolutions.co.uk ...

reusable data models for dashboards and performance monitoring. Managing the cloud data warehouse and ensuring data quality, reliability, and performance. Supporting the move towards MLOps capability, including versioning and reproducibility. SKILLS AND EXPERIENCE The successful Senior Data Engineer will have the following skills and experience: Strong commercial experience ...

reusable data models for dashboards and performance monitoring. Managing the cloud data warehouse and ensuring data quality, reliability, and performance. Supporting the move towards MLOps capability, including versioning and reproducibility. SKILLS AND EXPERIENCE The successful Senior Data Engineer will have the following skills and experience: Strong commercial experience ...

reusable data models for dashboards and performance monitoring. Managing the cloud data warehouse and ensuring data quality, reliability, and performance. Supporting the move towards MLOps capability, including versioning and reproducibility. SKILLS AND EXPERIENCE The successful Senior Data Engineer will have the following skills and experience: Strong commercial experience ...

Skills and Qualifications Experience working with cloud platforms such as Azure, AWS, or Google Cloud. Background in deploying machine learning models into production environments (MLOps experience is advantageous). Hands-on experience with big-data or distributed computing tools such as Spark and Databricks. Familiarity with visualisation tools such ...

Experience with machine learning frameworks including TensorFlow, PyTorch or Scikit-learn. Familiarity with cloud platforms such as AWS, Azure or Google Cloud and associated MLOps practices. Experience with automation and orchestration tooling such as UiPath, Airflow or Kubeflow. Experience and Capability Strong experience delivering AI or automation solutions within enterprise ...

security, ethical, and regulatory requirements. Deliver AI solutions that are robust, maintainable, and scalable. Required Skills Programming: Advanced proficiency in Python. ML Engineering & MLOps: Hands-on experience with widely used ML tooling (e.g., MLflow, Airflow, Docker, Kubernetes). CI/CD & DevOps: Familiarity with CI/CD workflows and automation ...

security, ethical, and regulatory requirements. Deliver AI solutions that are robust, maintainable, and scalable. Required Skills Programming: Advanced proficiency in Python. ML Engineering & MLOps: Hands-on experience with widely used ML tooling (e.g., MLflow, Airflow, Docker, Kubernetes). CI/CD & DevOps: Familiarity with CI/CD workflows and automation ...

R. Experience with machine learning frameworks and libraries (e.g. TensorFlow, PyTorch, Scikit-learn). Familiarity with cloud platforms (AWS, Azure or Google Cloud) and MLOps practices. Knowledge of automation technologies including RPA platforms (e.g. UiPath) and orchestration tools (Airflow, Kubeflow). Soft Skills: Excellent problem-solving and analytical capabilities. Strong ...

integration layers Contribute to UI/UX when needed as part of end-to-end delivery Ensure clean, scalable engineering across the stack MLOps/LLMOps Own the deployment, monitoring, and iteration of AI systems Use modern tooling to ensure models and pipelines are reliable, observable, and repeatable Collaboration Work ...

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 ...

GCP. A track record of building or scaling an AI/Automation strategy. Desirable extras include: Hands-on coding experience. Familiarity with MLOps or RPA tooling. Experience with advanced analytics, data engineering or architecture. Knowledge of industry compliance standards (ISO, Cyber Essentials). Experience with RPA platforms such as Robert ...

versioning) Nice to Have Background in data science or applied ML Experience building AI agents or intelligent automation Familiarity with cloud-native architectures and MLOps ...

automation Containerisation and orchestration Monitoring and observability tools Experience in the defence or advanced technology sector Experience with GPU based computer environments Experience with MLOps and associated tooling Experience with data pipelines Experience with Infrastructure as Code Experience with security integration in DevOps i.e. DevSecOps Service-oriented with effective communication ...

deploy, tune, and monitor our Large Language Model (LLM) and AI stack across primarily on-premise environments with selective cloud integrations. This role spans MLOps and platform engineering, and implements AI governance, ensuring our AI capabilities are secure, performant, compliant, and aligned to long-term enterprise strategy. Why BAE Systems ...

transformation and ETL pipelines and APIs Desirable Skills & Experience: Experience with graph databases and advanced query languages Knowledge of machine learning data pipelines and MLOps practices Familiarity with data virtualisation and data mesh concepts Experience with IaaC, containerisation and orchestration, BI/visualisation tools *Formal offers to successful candidate will ...

issues and implement effective resolutions. Optimize application performance using Azure monitoring tools (Azure Monitor, App Insights). Improve SQL query performance for applications and MLOps workflows. Perform proactive monitoring, troubleshooting, and enhancement of application functionality. Integration & Documentation Integrate third-party APIs/services ensuring seamless communication. Document technical decisions, architectural ...

concept to production Establish AI operating models, best practices, and responsible AI frameworks Build and lead high-performing multidisciplinary teams (Data Science, ML Engineering, MLOps) Identify use cases across functions (customer experience, operations, knowledge management, automation) Ensure scalability, security, and compliance of AI platforms Required Experience Proven leadership delivering Generative … deep learning, model optimisation Evaluation frameworks and guardrails Data & Platforms Vector databases (Pinecone, Weaviate, FAISS, Milvus) Knowledge graphs and semantic search Data engineering pipelines MLOps & Deployment CI/CD for ML, model monitoring, versioning Kubernetes, Docker, serverless architectures MLflow, Kubeflow, SageMaker or similar Cloud & Architecture Azure AI, AWS AI/ ...

Lead the implementation of Generative AI models, LLMs, and agentic frameworks. •Collaborate with stakeholders to define problem statements and solution approaches. •Deploy models using MLOps tools such as SageMaker, Snowflake, and CI/CD pipelines. •Integrate vector databases and Retrieval-Augmented Generation (RAG) pipelines. •Ensure high-quality delivery and adherence … Azure, GCP) and their AI/ML services. •Minimum 5 years in ML model development, data engineering, and software engineering. •Minimum 3 years in MLOps and AI/ML deployment. •Minimum **2 years in Generative AI, LLMs, and agentic frameworks. Preferred •Experience with API Gateway development and deployment on Azure ...