26 to 50 of 559 MLOps Jobs in England

algorithms Our technology stack Python and associated ML/DS libraries (Scikit-learn, Numpy, LightlGBM, Pandas, LangChain/LangGraph, TensorFlow, etc ) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc. MLOps: Terraform, Docker, Airflow, MLFlow More information: Enjoy fantastic perks like private healthcare & dental insurance, a generous work from abroad policy, 2-for-1 share purchase plans, extra festive time off More ❯

the platform, making the best use of available infrastructure Adapting existing solutions to use our inference service, ensuring a seamless transition What You Bring 5+ years working in an MLOps or related ML Engineering role Production experience self-hosting & operating LLMs at scale for generative tasks via an inference framework such as Ray or KServe (or similar) Production experience with More ❯

and deploy advanced machine learning and behavioural intelligence models. Lead the transition of prototypes into scalable, cloud-native production systems. Architect data pipelines and model-serving infrastructure (Docker, Kubernetes, MLOps). Work with large-scale time series and behavioural data from diverse sensors. Contribute to strategic technical decisions and mentor junior engineers. Collaborate cross-functionally with product, UX, and leadership … Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for ML, and model performance monitoring. A background in behavioural biometrics, human-computer interaction, or large-scale sensor/time-series data is a strong plus. A More ❯

and deploy advanced machine learning and behavioural intelligence models. Lead the transition of prototypes into scalable, cloud-native production systems. Architect data pipelines and model-serving infrastructure (Docker, Kubernetes, MLOps). Work with large-scale time series and behavioural data from diverse sensors. Contribute to strategic technical decisions and mentor junior engineers. Collaborate cross-functionally with product, UX, and leadership … Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for ML, and model performance monitoring. A background in behavioural biometrics, human-computer interaction, or large-scale sensor/time-series data is a strong plus. A More ❯

and deploy advanced machine learning and behavioural intelligence models. Lead the transition of prototypes into scalable, cloud-native production systems. Architect data pipelines and model-serving infrastructure (Docker, Kubernetes, MLOps). Work with large-scale time series and behavioural data from diverse sensors. Contribute to strategic technical decisions and mentor junior engineers. Collaborate cross-functionally with product, UX, and leadership … Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for ML, and model performance monitoring. A background in behavioural biometrics, human-computer interaction, or large-scale sensor/time-series data is a strong plus. A More ❯

attribution, predicting customer propensity, segmenting customer groups based on behavioral data, and recommending products and/or content. Fine-tune Large Language Models to business-specific use cases. Deploy MLOps pipelines together with our ML engineers. Work closely with data engineers, fellow data scientists/AI engineers, and consultants to ensure seamless integration and deployment of AI solutions that create … Excellent communication and problem-solving skills. Available to start working in the UK. Nice to Have Experience with natural language processing (NLP) or computer vision (CV). Knowledge of MLOps and model deployment pipelines. Familiarity with AI ethics and responsible AI principles. Experience working with large datasets and distributed computing. Contributions to open-source AI projects. We Offer Benefits vary More ❯

attribution, predicting customer propensity, segmenting customer groups based on behavioural data, and recommending products and/or content. Fine-tune Large Language Models to business-specific use cases. Deploy MLOps pipelines together with our ML engineers. Work closely with data engineers, fellow data scientists/AI engineers and consultants to ensure seamless integration and deployment of AI solutions that create … communication and problem-solving skills. Direct availability to start working in the UK. Nice to have: Experience with natural language processing (NLP) or computer vision (CV). Knowledge of MLOps and model deployment pipelines. Familiarity with AI ethics and responsible AI principles. Experience working with large datasets and distributed computing. Contributions to open-source AI projects. WE OFFER: The benefits More ❯

attribution, predicting customer propensity, segmenting customer groups based on behavioural data, and recommending products and/or content. Fine-tune Large Language Models to business-specific use cases. Deploy MLOps pipelines together with our ML engineers. Work closely with data engineers, fellow data scientists/AI engineers and consultants to ensure seamless integration and deployment of AI solutions that create … communication and problem-solving skills. Direct availability to start working in the UK. Nice to have: Experience with natural language processing (NLP) or computer vision (CV). Knowledge of MLOps and model deployment pipelines. Familiarity with AI ethics and responsible AI principles. Experience working with large datasets and distributed computing. Contributions to open-source AI projects. WE OFFER: The benefits More ❯

team helping to 'walk in the shoes' of application teams as well as operational engineering teams. Communicate progress, results, and insights to management and other stakeholders. Strong understanding of MLops principles and practices. Daily/Monthly Responsibilities Build and run responsibilities for GenAI ensuring robust support folding into standard incident processes as the products mature. Help work with distributed teams … and LLMs. An overall 8+ years of experience as Software Engineer. Proficiency in programming languages such as Python, TensorFlow, PyTorch, and other AI/ML frameworks. Strong understanding of MLops principles and practices. Ability to design and implement complex ML systems. Strong understanding of neural networks, natural language processing (NLP), computer vision, and other AI domains. Experience with cloud platforms More ❯

and Computer Vision Take ownership of developing, training and productionising machine learning lifecycles, adhering to best practices, security needs and quality assurance Development of neural networks Implementing and maintaining MLops workflows Work alongside Data Engineers and DevOps Engineers to ensure continuous integration and deployment of machine learning models in production. Proactive learning and researching new technologies and software versions Working … Knowledge of machine learning architectures, loss functions, tools and techniques Experience training machine learning models, including hyperparameter tuning and optimizing model performance Experience with (or at least exposure to) MLops workflows Experience with Python Experience with SQL Critical thinking and ability to problem solve Experience with data warehousing and database systems Exposure to working with CI/CD Knowledge of More ❯

and Computer Vision Take ownership of developing, training and productionising machine learning lifecycles, adhering to best practices, security needs and quality assurance Development of neural networks Implementing and maintaining MLops workflows Work alongside Data Engineers and DevOps Engineers to ensure continuous integration and deployment of machine learning models in production. Proactive learning and researching new technologies and software versions Working … Knowledge of machine learning architectures, loss functions, tools and techniques Experience training machine learning models, including hyperparameter tuning and optimizing model performance Experience with (or at least exposure to) MLops workflows Experience with Python Experience with SQL Critical thinking and ability to problem solve Experience with data warehousing and database systems Exposure to working with CI/CD Knowledge of More ❯

Points Additional skills that would be beneficial include: Experience in a startup environment Knowledge of Python frameworks (Django, Flask, FastAPI), Rust, and machine learning libraries Familiarity with Generative AI, MLOps, CI/CD, and cloud platforms (AWS/GCP/Azure) Expertise with container tools like Docker and Kubernetes Ready to take the next step in your engineering career? Apply More ❯

tools and cloud platforms (e.g., Azure, GCP, AWS) Knowledge of deep learning, NLP, and computer vision techniques, (especially in the context of Microsoft Copilot and OpenAI APIs) Familiarity with MLOps practices using tools like Azure ML Pipelines, MLflow, Docker, and Kubernetes Excellent problem-solving and analytical skills, with the ability to apply AI to legal challenges Bachelor's or master More ❯

Mistral. Model performance and optimization: Fine-tuning and optimizing LLMs for quality, latency, sustainability, and cost. Programming and NLP tools: Advanced Python, frameworks like PyTorch, TensorFlow, Hugging Face, LangChain. MLOps and deployment: Docker, Kubernetes, Azure ML Studio, MLFlow. Cloud and AI infrastructure: Experience with Azure Cloud for scalable deployment. Databases and data platforms: SQL, NoSQL, Snowflake, Databricks. OUR VALUES: CURIOSITY More ❯

pipelines. Familiarity with data lake architectures and tools like Delta Lake , LakeFS , or Databricks . Knowledge of security and compliance best practices (e.g., SOC2, ISO 27001). Exposure to MLOps platforms or frameworks (e.g., MLflow, Kubeflow, Vertex AI). What We Offer Competitive salary + equity Flexible work environment and remote-friendly culture Opportunities to work on cutting-edge AI More ❯

machine learning lifecycle, designing sophisticated models, experimenting with cutting edge techniques and building robust, production-ready pipelines. You will also contribute to the technical architecture, champion best practices in MLOps, and guide the strategic direction of our AI capabilities. This is a hands-on role for someone who enjoys both deep technical work and cross-functional collaboration—driving forward innovation More ❯

machine learning lifecycle, designing sophisticated models, experimenting with cutting edge techniques and building robust, production-ready pipelines. You will also contribute to the technical architecture, champion best practices in MLOps, and guide the strategic direction of our AI capabilities. This is a hands-on role for someone who enjoys both deep technical work and cross-functional collaboration—driving forward innovation More ❯

machine learning lifecycle, designing sophisticated models, experimenting with cutting edge techniques and building robust, production-ready pipelines. You will also contribute to the technical architecture, champion best practices in MLOps, and guide the strategic direction of our AI capabilities. This is a hands-on role for someone who enjoys both deep technical work and cross-functional collaboration—driving forward innovation More ❯

tuning, and workflow orchestration. Skilled in integrating LLMs with structured data systems (e.g., SQL databases, BigQuery) to enable natural language querying and advanced analytics. Proficient in designing and implementing MLOps/LLMOps pipelines for model deployment, monitoring, version control, and CI/CD workflows. Strong understanding of model performance evaluation, hyperparameter tuning, and maintenance using tools like Vertex AI Pipelines. More ❯

e.g. Git) Excellent knowledge of databases such as SQL/NoSQL Experience with at least one Cloud Provider (AWS, Azure or GCP) Strong experience deploying and monitoring machine learning (MLOps), using tools such as MLflow, AWS Sagemaker, and Azure Machine Learning Experience in relevant Data Manipulation, Machine Learning and Statistical Analysis coding packages (eg. in Python: NumPy, Scikit-Learn, Pandas More ❯

MLOps Engineers (Mid, Senior & Lead level) – UKIC DV Cleared | AI/ML Start-up | Manchester | Hybrid Are you an MLOps Engineer with active UKIC DV clearance looking to make a real-world impact at the cutting edge of AI and machine learning? We’re hiring Mid, Senior, and Lead MLOps Engineers for a fast-growing tech start-up at the … mission-critical domains. You’ll play a key role in designing and deploying robust ML infrastructure, supporting both public and private sector clients. What You'll Do as an MLOps Engineer: Deploy and manage machine learning models in production environments Build and optimise scalable MLOps pipelines using modern tools and cloud platforms (AWS, Azure, GCP) Work with tools like Terraform … Collaborate on high-impact, real-world AI/ML projects that truly make a difference Contribute ideas in a relaxed, open, and innovation-driven culture Location & Flexibility for the MLOps Engineer: Hybrid role based in Manchester Strong work-life balance and a genuinely fun, inclusive environment Excellent career progression , bonus structure What We're Looking For Most importantly, you must More ❯

MLOps Engineers (Mid, Senior & Lead level) – UKIC DV Cleared | AI/ML Start-up | Manchester | Hybrid Are you an MLOps Engineer with active UKIC DV clearance looking to make a real-world impact at the cutting edge of AI and machine learning? We’re hiring Mid, Senior, and Lead MLOps Engineers for a fast-growing tech start-up at the … mission-critical domains. You’ll play a key role in designing and deploying robust ML infrastructure, supporting both public and private sector clients. What You'll Do as an MLOps Engineer: Deploy and manage machine learning models in production environments Build and optimise scalable MLOps pipelines using modern tools and cloud platforms (AWS, Azure, GCP) Work with tools like Terraform … Collaborate on high-impact, real-world AI/ML projects that truly make a difference Contribute ideas in a relaxed, open, and innovation-driven culture Location & Flexibility for the MLOps Engineer: Hybrid role based in Manchester Strong work-life balance and a genuinely fun, inclusive environment Excellent career progression, bonus structure What We're Looking For Most importantly, you must More ❯

global impact, and ready to excel in a dynamic, high-energy environment. Join our team and help shape the future of Vision AI. 🌎 Location and Legalities This full-time MLOps Engineer position is based onsite in our brand-new Ultralytics office in London, UK. Applicants must have legal authorization to work in the UK, as Ultralytics does not provide visa … sponsorship. 🚀 What You'll Do As an MLOps Engineer at Ultralytics, you will build and manage the infrastructure that powers our cutting-edge AI models, from training to deployment. You will be at the heart of our operations, ensuring our machine learning lifecycle is efficient, scalable, and robust. Key responsibilities include: Designing, building, and maintaining our MLOps infrastructure on cloud … that our state-of-the-art models are accessible, reliable, and performant for our global user base. 🛠️ Skills and Experience 5+ years of experience in a DevOps, SRE, or MLOps role. Strong proficiency in Python and extensive experience with ML frameworks like PyTorch. Proven experience building and managing CI/CD pipelines for machine learning systems. Deep expertise with containerization More ❯

global impact, and ready to excel in a dynamic, high-energy environment. Join our team and help shape the future of Vision AI. 🌎 Location and Legalities This full-time MLOps Engineer position is based onsite in our brand-new Ultralytics office in London, UK. Applicants must have legal authorization to work in the UK, as Ultralytics does not provide visa … sponsorship. 🚀 What You'll Do As an MLOps Engineer at Ultralytics, you will build and manage the infrastructure that powers our cutting-edge AI models, from training to deployment. You will be at the heart of our operations, ensuring our machine learning lifecycle is efficient, scalable, and robust. Key responsibilities include: Designing, building, and maintaining our MLOps infrastructure on cloud … that our state-of-the-art models are accessible, reliable, and performant for our global user base. 🛠️ Skills and Experience 5+ years of experience in a DevOps, SRE, or MLOps role. Strong proficiency in Python and extensive experience with ML frameworks like PyTorch. Proven experience building and managing CI/CD pipelines for machine learning systems. Deep expertise with containerization More ❯

About the Role We are seeking a Senior MLOps Engineer to join our AI team and drive the design, deployment, and continuous improvement of our MLOps platform. In this role, you will have the autonomy to shape our infrastructure, ensuring scalable, efficient, and robust operations that support rapid model iteration and deployment at scale. Key Responsibilities: Design & Implement ML Workflows … Build and Scale Our MLOps Platform Design, develop, and optimise a high-throughput model inference system for production-grade AI. Create streamlined workflow pipelines for model training, testing, monitoring and deployment, leveraging cloud-native tools. Cloud & Container Management: Deploy and manage applications using AWS services, Kubernetes, Docker, and other DevOps best practices. LLM Deployment & Fine Tuning: Drive the deployment and … Collaborate Across Teams: Work closely with Machine Learning engineers to enable their delivery What We're Looking For: Our ideal candidate will have a strong background in machine learning, MLOps, and cloud technologies with hands-on experience across the following areas: Cloud & DevOps Expertise: Experience with AWS, Kubernetes, and Docker. Proven skills in designing and managing CI/CD pipelines More ❯