51 to 75 of 108 MLOps Jobs in the UK excluding London

AI Solutions, B2B, B2C, Azure, AI Foundry, Open-AI, Microsoft Copilot Studio, Machine Learning, Python, TensorFlow, PyTorch, scikit-learn, Large Language Models, LLM, Data preprocessing, REST API, Microservices architecture, MLOps, CI/CD for ML, Power-BI, Docker, Kubernetes, AI Ethics, Cloud Platforms, AWS, Google Cloud Platform, SQL, NoSQL, DevOps, Financial services, Regulatory environments Contract Type: Hybrid/Bedford Daily … with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn. Experience with Large Language Models, prompt engineering, and RAG implementations. Strong skills in data analytics, API development, and MLOps practices including CI/CD for ML. Excellent technical documentation and communication skills. Desirable knowledge in Docker, Kubernetes, and understanding of financial services or regulatory environments. In the first instance More ❯

Senior MLOps Engineer | Established Bank | £70,000-£ 85,000 base + Bonus | Hybrid We are looking for an experienced MLOps Engineer in London to join an established Banking client who have multiple offices around the UK. They have allocated a ton of investment to propel their AI & Cloud transformation and this role will be the first of its kind with … environments Automate pipelines and services (ETL, storage, databases) Collaborate with data scientists and engineers Explore new tools to boost ML performance and reliability What are we looking for? Solid MLOps or ML Engineering experience Strong Python & SQL skills Hands-on with AWS, Azure, Terraform Great communication & problem-solving skills Bonus: Familiarity with finance or data viz tools (Power BI/ More ❯

+ 10–20% bonus (linked to MVP pilot) Location: Slough (Hybrid - 2+ days/week) Stack: Python, LangChain, Semantic Kernel, vector DBs, Azure AI/MLOps Visa: No sponsorship available Interested? Please apply below. More ❯

so your impact will be visible, measurable, and far-reaching. You'll also play a key role in modernising and streamlining the platform's AI and data infrastructure, championing MLOps best practices, and aligning technical delivery with strategic goals. What You'll Bring Significant experience leading AI/ML teams in fast-paced, SaaS-driven environments Proven ability to deliver More ❯

a related field Experience with multi-modal models that combine vision and language Strong grasp of data-centric AI practices - annotation tooling, prompt evaluation, and dataset curation Familiarity with MLOps tools (e.g. Weights & Biases, SageMaker, MLflow) Experience working in regulated sectors like insurance, banking, or property What You'll Be Doing This is a hands-on, high-impact role - you More ❯

other engineers to build fast, and you'll use Python and Kubernetes to deploy systems in production. What you'll do Work with a high performance team of LLM, MLOps, backend and front end engineers Tackle the biggest problems facing the company, giving a wide experience across the business, with the freedom to define novel approaches Work to help LLMs More ❯

seek an adept expert to contribute significantly to our R&D team, bridging machine learning engineering with applied data science. You'll improve and manage our Machine Learning Operations (MLOps) on Azure, and participate in creating, assessing, and advancing various machine learning models and AI systems. Collaborate extensively with scientific and operational teams to guarantee the robustness, scalability, and reliability … informed decision-making and boost innovation. Help our CDMO's mission by turning research insights into practical solutions efficiently. Key responsibilities: Compose, construct, and uphold resilient machine learning operations (MLOps) pipelines that facilitate the complete lifecycle of AI models-from creation to implementation and supervision. Guarantee the successful deployment of machine learning and large language models (LLMs) in practical operational … interpret, share, and act on. Key requirements: MSc or BSc in Computer Science, Data Science, Bioinformatics, Engineering, or a related field, or equivalent experience. Proven experience designing and deploying MLOps pipelines (MLflow, Azure ML, Azure DevOps etc). Strong programming skills in Python and familiarity with common ML/AI libraries (scikit-learn, tensorflow, Keras etc.). Experience implementing machine More ❯

Senior MLOps Engineer – AI Consultancy | Manchester | £60k–£70k + Equity + Benefits We’re hiring a Senior MLOps Engineer to join a fast-growing AI consultancy based in Manchester City Centre (3 days on-site). If you're passionate about productionising machine learning and want to work on real-world AI challenges, this could be the role for you. … TensorFlow, PyTorch, Keras, SKLearn) Proficiency with Git, Unix/Linux, Docker Cloud experience (AWS, Azure, or similar) Excellent communication skills UK citizen eligible for SC clearance Nice to have: MLOps experience Open source contributions Curiosity for learning new tech Perks: £60k–£70k salary EMI share scheme Personal L&D budget 25 days holiday (rising to 30) Pension More ❯

modelling, integration patterns, and governance frameworks. Experience with BI tools (e.g., Power BI) and semantic modelling. Knowledge of data security, compliance (e.g., GDPR), and metadata management. Desirable: Experience with MLOps, streaming technologies, and regulated sectors. More ❯

for ML developments within a scaleup environment. What you’ll do: Architect and build scalable ML systems in GCP and AWS Drive end-to-end delivery across experimentation, modelling, MLOps and deployment Set technical direction, mentor teams, and champion best practices Work closely with product and data teams to turn ideas into real-world impact Collaborate with 3rd party vendors More ❯

for ML developments within a scaleup environment. What you’ll do: Architect and build scalable ML systems in GCP and AWS Drive end-to-end delivery across experimentation, modelling, MLOps and deployment Set technical direction, mentor teams, and champion best practices Work closely with product and data teams to turn ideas into real-world impact Collaborate with 3rd party vendors More ❯

for ML developments within a scaleup environment. What you’ll do: Architect and build scalable ML systems in GCP and AWS Drive end-to-end delivery across experimentation, modelling, MLOps and deployment Set technical direction, mentor teams, and champion best practices Work closely with product and data teams to turn ideas into real-world impact Collaborate with 3rd party vendors More ❯

for ML developments within a scaleup environment. What you’ll do: Architect and build scalable ML systems in GCP and AWS Drive end-to-end delivery across experimentation, modelling, MLOps and deployment Set technical direction, mentor teams, and champion best practices Work closely with product and data teams to turn ideas into real-world impact Collaborate with 3rd party vendors More ❯

for ML developments within a scaleup environment. What you’ll do: Architect and build scalable ML systems in GCP and AWS Drive end-to-end delivery across experimentation, modelling, MLOps and deployment Set technical direction, mentor teams, and champion best practices Work closely with product and data teams to turn ideas into real-world impact Collaborate with 3rd party vendors More ❯

for ML developments within a scaleup environment. What you’ll do: Architect and build scalable ML systems in GCP and AWS Drive end-to-end delivery across experimentation, modelling, MLOps and deployment Set technical direction, mentor teams, and champion best practices Work closely with product and data teams to turn ideas into real-world impact Collaborate with 3rd party vendors More ❯

stories, change requests, and screen designs. A background as a Business Analyst is preferred. Experience in workforce management, scheduling, HR tech, optimisation domains, AI/ML productisation, LLM integration, MLOps, or enterprise integration standards (ETL, REST APIs, webhooks, event streaming) is a bonus. At the centre of the company's culture is freedom and openness which takes a lot of More ❯

and vector search architectures Ability to build autonomous agents that interact with APIs, fetch public data and trigger external actions Experience deploying AI solutions on Azure Strong understanding of MLOps, data engineering and model life cycle management Experience embedding AI features into a SaaS or operational technology platform Experience working in the manufacturing industry or with manufacturing, supply chain or More ❯

BERT, T5). Solid background in data science and machine learning, including model development, training, evaluation, and deployment. Experience building and deploying chatbots or conversational AI systems. Knowledge of MLOps tools and pipelines for model versioning and deployment. If you are available and interested in a 6-month Outside IR35 contract, please apply in the first instance and you will More ❯

BERT, T5). Solid background in data science and machine learning, including model development, training, evaluation, and deployment. Experience building and deploying chatbots or conversational AI systems. Knowledge of MLOps tools and pipelines for model versioning and deployment. If you are available and interested in a 6-month Outside IR35 contract, please apply in the first instance and you will More ❯

Senior Machine Learning/AI Engineer Position Overview: We are seeking a Senior Machine Learning/AI Engineer with expertise in Databricks, MLOps/LLMOps, and cloud-native architecture . The candidate must have recent experience implementing data science solutions in Databricks and be comfortable deploying web applications via containerized workflows (Docker, Kubernetes). This role involves building scalable AI … in production. Key Responsibilities: Design, develop, and deploy ML, Deep Learning, and LLM solutions. Implement scalable ML and data pipelines in Databricks (PySpark, Delta Lake, MLflow). Build automated MLOps pipelines with model tracking, CI/CD, and registry. Deploy and operationalize LLMs , including fine-tuning, prompt optimization, and monitoring. Architect secure ML/AI systems on Azure, AWS, or … 5+ years in ML/AI solution development. Recent hands-on experience with Databricks, PySpark, Delta Lake, MLflow . Experience with LLMs (Hugging Face, LangChain, Azure OpenAI) . Strong MLOps, CI/CD, and model monitoring experience. Proficiency in Python, PyTorch/TensorFlow, FastAPI/Flask . Cloud architecture experience: Azure preferred, AWS/GCP acceptable . Skilled in Docker More ❯

and vector search architectures Ability to build autonomous agents that interact with APIs, fetch public data and trigger external actions Experience deploying AI solutions on Azure Strong understanding of MLOps, data engineering and model lifecycle management Experience embedding AI features into a SaaS or operational technology platform Experience working in the manufacturing industry or with manufacturing, supply chain or inventory More ❯

Data Science Engineer - MLOPS, Machine Learning, AI, Artificial Intelligence, Azure, PyTorch, TensorFlow, LangChain, OpenAI, Docker, Kubernetes, GenAI, ETL We are actively working with a global law firm who are actively looking to bolster their IT team as they undergo a global-scale cloud transformation. At present they are looking to take on a new Data Science Engineer (MLOPS, Machine Learning … tier global law firm who have a long-stream of projects in the pipeline alongside a diverse and collaborative team environment. To be considered for this Data Science Engineer (MLOPS, Machine Learning, AI, Artificial Intelligence, Azure, PyTorch, TensorFlow, LangChain, OpenAI, Docker, Kubernetes, GenAI, ETL) role, it's ideal you have: Ideal but not required law firm experience 2-4 years … science and AI solutions end-to-end, from design and development through testing, release, monitoring, and support. Operationalize models with CI/CD pipelines, automated testing, and monitoring, applying MLOps practices such as versioning, retraining, and drift detection (tools: MLflow, Azure ML, Databricks) Leverage both open-source frameworks (LangChain, Hugging Face, etc.) and enterprise platforms (Azure OpenAI, Databricks, etc.) to More ❯

which we work and live. It is personal to all of us.” – Julie Sweet, Accenture CEO. We are a dynamic team of specialists in Data Science, Data Engineering, and MLOps, dedicated to delivering cutting-edge AI solutions within secure government and defence environments. Join us to be part of an inclusive and collaborative environment where innovation thrives, and continuous learning More ❯

which we work and live. It is personal to all of us.” – Julie Sweet, Accenture CEO We are a dynamic team of specialists in Data Science, Data Engineering, and MLOps, dedicated to delivering cutting-edge AI solutions within secure government and defence environments. Join us to be part of an inclusive and collaborative environment where innovation thrives, and continuous learning More ❯

Scientists, Data Engineers, and DevSecOps teams , building automation pipelines that accelerate model development and deployment across distributed, cloud-native systems. Key Responsibilities Design, implement, and maintain end-to-end MLOps pipelines for model training, validation, deployment, and monitoring. Develop and automate workflows using Terraform, Kubernetes, Docker , and CI/CD toolchains (GitHub Actions, Jenkins, Argo, etc.). Manage scalable cloud … pipelines. Contribute to the development of a modular, reusable ML platform architecture supporting multi-modal data (genomic, clinical, imaging, etc.). Essential Skills and Experience Proven experience as an MLOps Engineer, Platform Engineer, or DevOps Engineer supporting ML or data science teams. Strong hands-on experience with containerization (Docker) and orchestration (Kubernetes) . Expertise in Terraform , Infrastructure as Code (IaC … Solid understanding of CI/CD pipelines and automated testing frameworks. Experience with ML frameworks such as PyTorch, TensorFlow, or Scikit-learn. Familiarity with MLflow, Kubeflow, DVC, or similar MLOps tools . Understanding of cloud security principles , IAM, and networking best practices. Proficiency in Python and Bash scripting for automation and tooling development. Version control with Git , and collaborative development More ❯