26 to 50 of 344 MLOps Jobs in England

using frameworks such as Transformers, PyTorch, or TensorFlow. Strong Python skills, with the ability to write clean, modular, production-grade code, and a solid understanding of data engineering and MLOps principles. Ability to lead end-to-end ML projects, work independently in ambiguous problem spaces, and mentor junior team members. Strong collaboration and communication skills, with experience aligning technical approaches More ❯

the ability to balance research innovation and commercial value delivery. Comfortable operating across cloud environments (GCP, Azure, AWS) and deploying AI/ML systems at scale. Strong knowledge of MLOps practices and infrastructure including CI/CD, model versioning, orchestration, and monitoring. A collaborative and inspiring leader who brings out the best in technical teams and communicates complex concepts to More ❯

Not Essential): Familiarity with deep 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 and remote work 📈 Career Growth : Structured More ❯

Not Essential): Familiarity with deep 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 and remote work 📈 Career Growth : Structured More ❯

5+ years of experience in technical product management Experience working with developer teams and productionizing AI or other data-intensive applications Breadth of knowledge or familiarity with GenAI platforms, MLOps platforms, AI toolkits Deep understanding of software development best practices Organizational and communication skills to effectively coordinate and work with engineers, UX, subject matter experts, other product managers, and senior More ❯

have 5+ years of experience in technical product management Experience working with developerteams and productionizing AI or other data-intensive applications Breadth of knowledge or familiarity with GenAI platforms, MLOps platforms, AI toolkits Deep understanding of software development best practices Organizational and communication skills to effectively coordinate and work with engineers, UX, subject matter experts, other product managers, and senior More ❯

a customer facing role 2+ years experience in a data-driven role, with exposure to software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps) Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow) Distributed computing frameworks (e.g., Spark, Dask) Cloud platforms (e.g., AWS, Azure, GCP) and HP More ❯

/entity relationships, NoSQL, JSON, XML, SQL and exposure to data visualisation tools (ETL/ELT). Data Science Tools: Proficiency in Numpy, Pandas, Matplotlib, Seaborn and Scikit-learn. MLOps: Experience building pipelines (CI/CD) using Bicep or similar technologies. Expertise in deploying, monitoring and managing machine learning models in production environments. API Development: An understanding of REST. Experience More ❯

Microsoft Azure AI services. Strong understanding of large language models, prompt engineering, and fine-tuning techniques. Experience with data manipulation libraries (e.g., Pandas, NumPy) and cloud platforms. Familiarity with MLOps, version control (e.g., Git), and deployment tools (e.g., Docker, Kubernetes). Excellent problem-solving skills and the ability to work on complex AI challenges. Nice to Have: Experience with NLP More ❯

scalable systems and high-volume, low latency, transaction/computation applications. Broad understanding of the software development lifecycle, including the application of LLM driven and Data Science DevOps/MLOps/AIOps methodologies. Expertise in data management and analytics, including data structures, data processing, data modelling, and statistical analysis. Knowledge of Python and C# for development and scripting. Leadership: Proven More ❯

scalable systems and high-volume, low latency, transaction/computation applications. Broad understanding of the software development lifecycle, including the application of LLM driven and Data Science DevOps/MLOps/AIOps methodologies. Expertise in data management and analytics, including data structures, data processing, data modelling, and statistical analysis. Knowledge of Python and C# for development and scripting. Leadership: Proven More ❯

teams and mentor junior practitioners Ability to communicate complex technical concepts clearly to non-technical audiences Bonus Points For Participation in Kaggle or other data science competitions Experience with MLOps practices (CI/CD, model monitoring, DevOps integration) Familiarity with advanced NLP frameworks such as spaCy or Transformers MSc or PhD in a numerate discipline Financial services or banking experience More ❯

translate technical work into business outcomes and influence stakeholders at all levels. Extra Awesome Experience managing hybrid teams that include both Data Scientists and ML Engineers Exposure to modern MLOps tooling (e.g. MLflow, Feature Store, SageMaker, Vertex AI) Familiarity with unstructured data modeling (e.g. NLP, embeddings, LLMs) and GenAI product patterns Experience working in product-led or B2B SaaS environments More ❯

organizations. You have experience developing state-of-the-art deep learning models, LLMs, and advanced AI architectures . You are an industry expert in ML model development, deployment, and MLOps at scale . You are deeply comfortable with Python, SQL, and ML frameworks (e.g., TensorFlow, PyTorch) and have experience working in a microservices architecture (Go Lang experience is a plus More ❯

models (Hugging Face, PyTorch, TensorFlow) with a strong grounding in evaluating NLP models using classification and ranking metrics, and experience running A/B or offline benchmarks. Proficient with MLOps and training infrastructure (MLflow, Kubeflow, Airflow), including CI/CD, hyperparameter tuning, and model versioning. Strong social media data extraction and scraping skills at scale (Twitter v2, Reddit, Discord, Telegram More ❯

experience in DevOps engineering Solid knowledge of cloud platforms, e.g. Azure/AWS/GCP (mandatory) Mastery of Docker architecture, containerization, and CI/CD tools Proven experience in MLOps practices, integrating machine learning models into scalable, secure production environments is a great plus Comfortable working with Bitbucket, Git, Confluence, and Jira Familiarity with platforms like Databricks is a strong More ❯

small & agile development team focused on building out a greenfield AI-powered transaction monitoring platform. You'll work on everything from ML model development and GenAI summarisation pipelines to MLOps and multi-agent systemswith real-world impact on financial security and compliance. What Youll Do: Develop and deploy machine learning models for anti-money laundering and counter-terrorist financing. Contribute More ❯

based workflows. Strong problem-solving mindset and a proactive approach to automation and scaling. Ability to communicate clearly and collaborate across cross-functional teams. Nice to Have Familiarity with MLOps tools such as MLflow, DVC, Airflow, or Kubeflow. Experience working with large language models or other Generative AI tools. Exposure to agentic AI concepts and implementations. Knowledge of cloud infrastructure More ❯

working in B2C, e-commerce, subscription, retail, or fintech industries is a strong advantage Nice to Have Experience with NLP for customer feedback or support ticket analysis Exposure to MLOps for model deployment and monitoring Familiarity with tools like Amplitude, Mixpanel, or Google Analytics Why Join Us? Shape data-driven strategy for how we understand and engage with our customers More ❯

working in B2C, e-commerce, subscription, retail, or fintech industries is a strong advantage Nice to Have Experience with NLP for customer feedback or support ticket analysis Exposure to MLOps for model deployment and monitoring Familiarity with tools like Amplitude, Mixpanel, or Google Analytics Why Join Us? Shape data-driven strategy for how we understand and engage with our customers More ❯

Actions, ArgoCD) Ability to lead delivery in agile environmentsbalancing scope, prioritisation, and quality Excellent communication and collaboration skills across technical and non-technical stakeholders A background in software engineering, MLOps, or data engineering with production ML experience Nice to have: Familiarity with streaming or event-driven ML architectures (e.g. Kafka, Flink, Spark Structured Streaming) Experience working in regulated domains such More ❯

machine learning solutions for performance and scalability. Custom Code: Implement tailored machine learning code to meet specific needs. Data Engineering: Ensure efficient data flow between databases and backend systems. MLOps : Automate ML workflows, focusing on testing, reproducibility, and feature/metadata storage. ML Architecture Design: Create machine learning architectures using Google Cloud tools and services. Engineering Software for Production: Build More ❯

or Azure SQL Database is beneficial. Experience in designing and maintaining robust CI/CD pipelines, applying Infrastructure as Code (IaC) principles with exposure to Terraform, and incorporating Azure MLOps practices for seamless deployment, versioning, and traceability of AI models and data Knowledge of DevSecOps principles and data governance best practices to secure AI infrastructure and ensure compliance. The ability More ❯

or Azure SQL Database is beneficial. Experience in designing and maintaining robust CI/CD pipelines, applying Infrastructure as Code (IaC) principles with exposure to Terraform, and incorporating Azure MLOps practices for seamless deployment, versioning, and traceability of AI models and data Knowledge of DevSecOps principles and data governance best practices to secure AI infrastructure and ensure compliance. The ability More ❯

marketing performance managers. Experience in Python and SQL. Experience with cloud platforms such as Amazon Web Services, Azure, or Google Cloud Platform. Deep understanding of Generative AI, NLP, and MLOps concepts. Analytical, flexible, independent, and a strong communicator. WE OFFER: A flexible, hybrid working policy (2 days from the office, depending on location). An excellent salary based on experience More ❯