151 to 175 of 435 MLOps Jobs in England

and pre-sales activities Maintain high billable utilisation while delivering exceptional client value Contribute to Made Tech's thought leadership in AI/ML Guide clients in building robust MLOps practices and data-driven cultures Hiring and line-managing data scientists and analysts Security Clearance An increasing number of our customers are specifying a minimum of SC (security check) clearance More ❯

Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human More ❯

Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human More ❯

Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human More ❯

Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human More ❯

MLOPS ENGINEER LONDON - HYBRID £80,000 - £95,000 This is a great opportunity for an MLOps engineer from a DevOps background with ML experience to drive cutting-edge work at a data-driven retail tech start-up! ROLE: In this role you will: Design, deploy and scale on their cloud platform (AWS/GCP) Implement and maintain CI/CD … pipelines Engineering data working closely with the Computer Vision team Deploying APIs and packages Stay updated on emerging technologies, trends, and best practices in DevOps and MLOps to recommend and implement innovative solutions that drive business value. Tech stack: Python, AWS/GCP, Docker, CI/CD, Deep Learning, Kubernetes, DevOps REQUIREMENTS: MSc in a numerical or relevant field is … preferred MLOps experience is required An excellent understanding of DevOps processes and techniques Happy working in a fast-paced environment Any experience working with computer vision engineers is a bonus! How To Apply Please register your interest for this role by sending your CV to Joseph Gregory via the apply link on this page. More ❯

MLOPS ENGINEER LONDON - HYBRID £80,000 - £95,000 This is a great opportunity for an MLOps engineer from a DevOps background with ML experience to drive cutting-edge work at a data-driven retail tech start-up! ROLE: In this role you will: Design, deploy and scale on their cloud platform (AWS/GCP) Implement and maintain CI/CD … pipelines Engineering data working closely with the Computer Vision team Deploying APIs and packages Stay updated on emerging technologies, trends, and best practices in DevOps and MLOps to recommend and implement innovative solutions that drive business value. Tech stack: Python, AWS/GCP, Docker, CI/CD, Deep Learning, Kubernetes, DevOps REQUIREMENTS: MSc in a numerical or relevant field is … preferred MLOps experience is required An excellent understanding of DevOps processes and techniques Happy working in a fast-paced environment Any experience working with computer vision engineers is a bonus! How To Apply Please register your interest for this role by sending your CV to Joseph Gregory via the apply link on this page. More ❯

Engineering Manager (Data MLOps AI Machine Learning) London/Remote to £110k Are you a data savvy hands-on technology leader? You could be joining a well-funded and growing hotel revenue optimisation technology start-up that uses AI and complex algorithms to enable hotels to price their rooms according to demand; this is a £7 billion a year industry … in it for you: Salary to £110k + bonus Pension Healthcare Flexible, remote working Training and career progression Apply now to find out more about this Engineering Manager (Data MLOps AI Machine Learning) opportunity. At Client Server we believe in a diverse workplace that allows people to play to their strengths and continually learn. We're an equal opportunities employer More ❯

We believe that we are better together, and at Tripadvisor we welcome you for who you are. Our workplace is for everyone, as is our people powered platform. At Tripadvisor, we want you to bring your unique perspective and experiences More ❯

We believe that we are better together, and at Tripadvisor we welcome you for who you are. Our workplace is for everyone, as is our people powered platform. At Tripadvisor, we want you to bring your unique perspective and experiences More ❯

Senior Machine Learning & MLOps Engineer 💰 £110,000-£120,000 + up to 10% bonus 🖥️ MLOps, Python, Terraform 🌍 London, one day a week in office 🦄 UK tech unicorn We are partnered with one of the UK's most profitable and exciting Insurtech companies who have reached a valuation of over $1BN. This will be their first ML/MLOps Engineering hire … warehouses like Snowflake. Version control: You are proficient with git. If you are interested in finding out more, please apply or contact me directly! 📧 jordanf@burnssheehan.co.uk Senior Machine Learning & MLOps Engineer 💰 £110,000-£120,000 + up to 10% bonus 🖥️ MLOps, Python, Terraform 🌍 London, one day a week in office 🦄 UK tech unicorn More ❯

Senior Machine Learning & MLOps Engineer 💰 £110,000-£120,000 + up to 10% bonus 🖥️ MLOps, Python, Terraform 🌍 London, one day a week in office 🦄 UK tech unicorn We are partnered with one of the UK's most profitable and exciting Insurtech companies who have reached a valuation of over $1BN. This will be their first ML/MLOps Engineering hire … warehouses like Snowflake. Version control: You are proficient with git. If you are interested in finding out more, please apply or contact me directly! 📧 jordanf@burnssheehan.co.uk Senior Machine Learning & MLOps Engineer 💰 £110,000-£120,000 + up to 10% bonus 🖥️ MLOps, Python, Terraform 🌍 London, one day a week in office 🦄 UK tech unicorn More ❯

cutting-edge machine learning solutions that influence decision-making across a large, fast-moving business. You'll have access to vast datasets, modern tooling, and the support of experienced MLOps and Data Engineering teams – freeing you to focus on model innovation , business impact , and team leadership . Key Responsibilities Lead and coach a team of data scientists focused on pricing … senior stakeholders to prioritise and deliver key initiatives. Work cross-functionally with Marketing and Operations data teams to extend the reach of data science across the organisation. Collaborate with MLOps and Engineering teams to ensure seamless product delivery and integration. Promote the use and value of pricing models to non-technical stakeholders through clear and effective communication. Continuously improve the … flexible hybrid work model (Reading or London) and a collaborative environment. A role where your models directly shape pricing, influence profitability, and deliver real commercial outcomes. Support from seasoned MLOps and engineering teams – letting you focus on research, modelling, and innovation . If you’re passionate about pricing science and ready to step into a leadership role where your work More ❯

cutting-edge machine learning solutions that influence decision-making across a large, fast-moving business. You'll have access to vast datasets, modern tooling, and the support of experienced MLOps and Data Engineering teams – freeing you to focus on model innovation , business impact , and team leadership . Key Responsibilities Lead and coach a team of data scientists focused on pricing … senior stakeholders to prioritise and deliver key initiatives. Work cross-functionally with Marketing and Operations data teams to extend the reach of data science across the organisation. Collaborate with MLOps and Engineering teams to ensure seamless product delivery and integration. Promote the use and value of pricing models to non-technical stakeholders through clear and effective communication. Continuously improve the … flexible hybrid work model (Reading or London) and a collaborative environment. A role where your models directly shape pricing, influence profitability, and deliver real commercial outcomes. Support from seasoned MLOps and engineering teams – letting you focus on research, modelling, and innovation . If you’re passionate about pricing science and ready to step into a leadership role where your work More ❯

cutting-edge machine learning solutions that influence decision-making across a large, fast-moving business. You'll have access to vast datasets, modern tooling, and the support of experienced MLOps and Data Engineering teams – freeing you to focus on model innovation , business impact , and team leadership . Key Responsibilities Lead and coach a team of data scientists focused on pricing … senior stakeholders to prioritise and deliver key initiatives. Work cross-functionally with Marketing and Operations data teams to extend the reach of data science across the organisation. Collaborate with MLOps and Engineering teams to ensure seamless product delivery and integration. Promote the use and value of pricing models to non-technical stakeholders through clear and effective communication. Continuously improve the … flexible hybrid work model (Reading or London) and a collaborative environment. A role where your models directly shape pricing, influence profitability, and deliver real commercial outcomes. Support from seasoned MLOps and engineering teams – letting you focus on research, modelling, and innovation . If you’re passionate about pricing science and ready to step into a leadership role where your work More ❯

and data science solutions for a diverse client base. Role Responsibilities Design and implement ML and Generative AI models to address client challenges Work closely with data engineers and MLOps professionals to deliver production-ready systems Apply techniques such as large language models (LLMs), retrieval-augmented generation (RAG), vector databases, prompt engineering, and model fine-tuning Engage with client stakeholders … Generative AI projects from concept to deployment Hands-on experience with frameworks such as Hugging Face, LangChain, and open-source LLMs Familiarity with tools such as Databricks and modern MLOps workflows Strong Python skills and familiarity with common data science tools and libraries Experience with cloud platforms (preferably Azure, but AWS or GCP also valuable) Confident communicating complex technical ideas More ❯

and data science solutions for a diverse client base. Role Responsibilities Design and implement ML and Generative AI models to address client challenges Work closely with data engineers and MLOps professionals to deliver production-ready systems Apply techniques such as large language models (LLMs), retrieval-augmented generation (RAG), vector databases, prompt engineering, and model fine-tuning Engage with client stakeholders … Generative AI projects from concept to deployment Hands-on experience with frameworks such as Hugging Face, LangChain, and open-source LLMs Familiarity with tools such as Databricks and modern MLOps workflows Strong Python skills and familiarity with common data science tools and libraries Experience with cloud platforms (preferably Azure, but AWS or GCP also valuable) Confident communicating complex technical ideas More ❯

and data science solutions for a diverse client base. Role Responsibilities Design and implement ML and Generative AI models to address client challenges Work closely with data engineers and MLOps professionals to deliver production-ready systems Apply techniques such as large language models (LLMs), retrieval-augmented generation (RAG), vector databases, prompt engineering, and model fine-tuning Engage with client stakeholders … Generative AI projects from concept to deployment Hands-on experience with frameworks such as Hugging Face, LangChain, and open-source LLMs Familiarity with tools such as Databricks and modern MLOps workflows Strong Python skills and familiarity with common data science tools and libraries Experience with cloud platforms (preferably Azure, but AWS or GCP also valuable) Confident communicating complex technical ideas More ❯

to-service communication, API gateways , and data management . AI & Machine Learning Platform: AI is a critical component of the product. You will lead the product vision for our MLOps pipelines and the integration of both traditional and generative AI models into our platform. DevOps & Automation: You will be responsible for the product strategy that underpins engineering enablement. This includes … AWS , and system architecture design. Deep understanding of microservices , Docker , security best practices, DevOps principles, CI/CD , and system monitoring. Direct experience with AI/ML products, including MLOps and the productization of machine learning models (both traditional and generative). Proven ability to bridge business and technical perspectives to make informed trade-offs between speed, quality, and scalability. More ❯

to-service communication, API gateways , and data management . AI & Machine Learning Platform: AI is a critical component of the product. You will lead the product vision for our MLOps pipelines and the integration of both traditional and generative AI models into our platform. DevOps & Automation: You will be responsible for the product strategy that underpins engineering enablement. This includes … AWS , and system architecture design. Deep understanding of microservices , Docker , security best practices, DevOps principles, CI/CD , and system monitoring. Direct experience with AI/ML products, including MLOps and the productization of machine learning models (both traditional and generative). Proven ability to bridge business and technical perspectives to make informed trade-offs between speed, quality, and scalability. More ❯

to-service communication, API gateways , and data management . AI & Machine Learning Platform: AI is a critical component of the product. You will lead the product vision for our MLOps pipelines and the integration of both traditional and generative AI models into our platform. DevOps & Automation: You will be responsible for the product strategy that underpins engineering enablement. This includes … AWS , and system architecture design. Deep understanding of microservices , Docker , security best practices, DevOps principles, CI/CD , and system monitoring. Direct experience with AI/ML products, including MLOps and the productization of machine learning models (both traditional and generative). Proven ability to bridge business and technical perspectives to make informed trade-offs between speed, quality, and scalability. More ❯

Azure ML Studio and Azure DevOps. Effective Communication: Present findings clearly through visualisation and reporting, including interactive dashboards and web applications using Power BI, R Shiny, or Python Flask. MLOps Maintenance: Maintain and enhance MLOps pipelines, focusing on model robustness and performance. Project Tracking: Manage code and project tracking using Git and Azure DevOps Boards, aligned with Scaled Agile Framework … a candidate with a blend of essential skills and experience, including: Hands-On Experience: Proven experience in data science and machine learning model deployment, preferably with Azure ML Studio. MLOps Proficiency: Strong understanding of pipeline management and model versioning. Data Manipulation Skills: Expertise in data extraction, transformation, and reshaping using SQL, R/Tidyverse, and Python/Pandas. visualisation Expertise More ❯

to production. Build robust APIs and microservices to serve AI models at scale. Integrate behavioural intelligence models across cloud platforms (AWS, GCP, Azure). Set up end-to-end MLOps pipelines: monitoring, retraining, and automation. Collaborate with cross-functional teams to align tech with user-centric product design. What We’re Looking For: 2+ years in AI/ML engineering … backend software roles with ML components. Proficiency in Python and frameworks like PyTorch/TensorFlow, Scikit-learn. Experience deploying models with Docker, Kubernetes, or serverless architectures. Solid grasp of MLOps workflows, versioning, and cloud automation. Strong foundations in algorithms, data structures, and system design. Bonus: Familiarity with behavioural biometrics, sensor-based or time series data An entrepreneurial mindset—curious, autonomous More ❯

core AI platform capabilities, supporting a Machine Learning Engineer on classical ML projects, and building the foundation for a future Data Science function. You will also define LLMOps and MLOps practices and ensure the infrastructure is in place to support long-term AI success across the business. Key Responsibilities: Strategy & Leadership Collaborate over the AI roadmap across GenAI, ML, and … lifecycle automation. Maintain awareness of emerging models and integration strategies. Machine Learning Engineering: Support the ML Engineer in model development, deployment, and monitoring. Contribute to pipelines, experimentation design, and MLOps enablement. Provide code and architectural reviews, as well as technical mentoring. Data Science Enablement Act as Data Scientist to support analytics and decision-making needs. Develop experimentation frameworks, metric definitions … and deploying GenAI applications in production. Strong hands-on knowledge of LLMs, prompt engineering, and retrieval-augmented generation (RAG). Practical experience with traditional ML, including data pipelines and MLOps workflows. Working knowledge of statistical modelling and experimentation. Proficiency in Python and at least one additional general-purpose language. Strong understanding of cloud-native architectures (AWS preferred). Experience leading More ❯

the process) Key Responsibilities: Design and build enterprise-grade AI and data platforms tailored to a broad range of use cases. Lead platform architecture work spanning cloud, data, DevOps, MLOps and LLMOps domains. Contribute to full software development lifecycle with a strong focus on performance and maintainability. Collaborate cross-functionally with consulting and engineering teams to guide best practices. Drive … as Databricks, Airflow, dbt, Snowflake, GitHub CI/CD, and infrastructure-as-code. Strong background across at least several of the following areas: Cloud Engineering, Data Platform Architecture, DevOps, MLOps/LLMOps. Ideal Profile: Proven track record designing AI-ready infrastructure and platform components. Enjoys solving complex problems collaboratively and influencing technical strategy. Effective in fast-paced environments with direct More ❯