1 to 25 of 163 MLOps Jobs in the UK

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 ...

frameworks, and modern AI workflows Experience with cloud platforms (AWS, GCP, or Azure) Understanding of distributed systems and large-scale data pipelines Experience with MLOps, CI/CD, and microservices architecture Familiarity with AI-assisted or agent-based development tools Strong stakeholder collaboration and communication skills Agile/Scrum experience ...

call/contact-centre analytics, Microsoft Teams Graph API, or telephony platforms (e.g. 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. Why Akixi ...

validation techniques to improve training pipelines Ensure data privacy and governance standards suitable for financial services Engineering best practices Contribute to DevOps and MLOps pipelines Implement robust version control, testing and CI/CD workflows Support reliable deployment and monitoring of models in production environments Technical leadership Mentor engineers ...

iterate). · Exposure to: LangChain and LangSmith/LangFuse Supervised fine-tuning or lightweight tuning (LoRA, PEFT) RAG evaluation techniques and model feedback loops MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes) · Familiarity with: AgentOps concepts (agent evaluation, monitoring) Basic telemetry/observability workflows (OpenTelemetry) Understanding of how domain-specific ...

future of AI, ML, and cloud innovation. Your next big opportunity starts here! For more details, visit : Website or LinkedIn Page . Role: MLOps Architect - AWS Experience Level: 8+ years Employment type: Full Time Location: Remote (UK) Description: We are seeking an experienced MLOps/AIOps Architect who can drive … implementation of MLOps strategy and also contribute broadly across other enterprise AI/ML programs. This role demands a strong architectural mindset, hands-on technical depth, and the ability to design scalable, cloud-native machine learning operations across traditional ML and modern LLM workflows. The ideal candidate will bring experience ...

Experience working with major cloud platforms such as AWS, Azure, or GCP. Familiarity with containerisation and orchestration technologies (e.g. Docker, Kubernetes). Exposure to MLOps practices or deploying AI/ML models into production environments. Experience working in agile or fast-paced delivery teams . ...

learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits: Competitive Salary & Bonus : £35,000 – £45,000 plus bonus Hybrid Working : A flexible mix of office ...

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 ...

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. ...

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 ...

fast-paced environment Nice to Have Experience within financial services or other regulated industries Exposure to vector databases (e.g. Pinecone, Weaviate, FAISS) Experience with MLOps/LLMOps and deploying models into production Familiarity with LLM fine-tuning, evaluation, or guardrailing techniques Experience building internal tools such as copilots or knowledge ...

/CD and infrastructure as code. • Experience of optimising systems for performance and scalability and reliability. • Understanding of machine learning workflows or MLOps for deploying and monitoring models in production. • Experience with cloud platforms, especially AWS and its data services (e.g., BigQuery, Redshift, Athena). • Knowledge of network protocols ...

Strong technical skills in Python, Java/Go, TensorFlow, PyTorch, and data engineering. Proven ability to engage directly with CxO-level stakeholders. Experience in MLOps, AI governance, and large-scale deployment. Recognised professional certifications in AI or cloud technologies. If you have these skills and would like to find ...

Owning ML models and pipelines that extract structured knowledge from complex, unstructured documents at scale. ▸ NLP · Document AI · Data Pipelines · Evals 3. Staff SE – MLOps/DevOps for AI Shaping the infrastructure behind model serving, training pipelines, LLMOps, and AgentOps across the full AI stack. ▸ MLFlow · Databricks · Datadog · Terraform ────────────────────────── What ...

Owning ML models and pipelines that extract structured knowledge from complex, unstructured documents at scale. ▸ NLP · Document AI · Data Pipelines · Evals 3. Staff SE – MLOps/DevOps for AI Shaping the infrastructure behind model serving, training pipelines, LLMOps, and AgentOps across the full AI stack. ▸ MLFlow · Databricks · Datadog · Terraform ────────────────────────── What ...

LLMs, prompt engineering, RAG, vector databases, evaluation, and security. Hands-on experience with fine-tuning, deploying, and monitoring large-scale GenAI systems. Strong MLOps/LLMOps capability: CI/CD, monitoring, governance. Cloud expertise across AWS, Azure, and/or GCP (cloud-agnostic preferred). Ability to communicate complex ...

systems Experience working with cloud platforms (AWS, GCP, or Azure) Understanding of distributed systems and scalable architectures Experience with CI/CD, microservices, and MLOps practices Ability to mentor and support engineers Strong collaboration and communication skills Experience working in Agile environments Degree in a relevant technical field (or equivalent ...

/CD and infrastructure as code. • Experience of optimising systems for performance and scalability and reliability. • Understanding of machine learning workflows or MLOps for deploying and monitoring models in production. • Experience with cloud platforms, especially AWS and its data services (e.g., BigQuery, Redshift, Athena). • Knowledge of network protocols ...

/CD and infrastructure as code. • Experience of optimising systems for performance and scalability and reliability. • Understanding of machine learning workflows or MLOps for deploying and monitoring models in production. • Experience with cloud platforms, especially AWS and its data services (e.g., BigQuery, Redshift, Athena). • Knowledge of network protocols ...

model artifacts, and inference outputs. Maintain audit trails for model decisions, data access, and deployment history. Attributes Required Qualifications 4+ years of experience in MLOps, ML Engineering, DevOps, or a closely related infrastructure role. Strong proficiency in Python for ML pipeline development, tooling, and automation. Hands-on experience with ...

Azure or Google Cloud** Data platforms including **Databricks, Snowflake or BigQuery** Python and modern ML frameworks Generative AI, LLM integration and RAG pipelines MLOps tooling and modern ML lifecycle management. The profile Experience designing enterprise AI or data platforms in complex technology environments. A background delivering large-scale transformation programmes ...

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 ...

move from legacy and hybrid platforms to a modern Fabric setup Supporting BI teams with semantic models, datasets and performance optimisation Enabling ML and MLOps workflows, from feature engineering to deployment Working closely with data scientists, analysts, IT and the wider business Embedding data quality, governance and best-practice standards ...

professional accreditation such as CEng. Experience with graph databases and advanced query languages (e.g., Neo4j, Gremlin). Knowledge of machine learning data pipelines and MLOps practices. Familiarity with data virtualisation and data mesh concepts. Hands-on experience with containerisation and orchestration (Docker, Kubernetes, Red Hat OpenShift and Ceph). Exposure ...