1 to 25 of 403 MLOps Jobs in England

Description We are looking for highly skilled and experienced Senior MLOps Engineer to join our team. This role will be involved in designing, implementing, and maintaining robust and scalable machine learning pipelines. This person will possess a strong background in DevOps practices, machine learning principles, and cloud computing platforms. You will work closely with data scientists and software engineers to … tune ML models for performance and accuracy. Understanding of statistical analysis and experimental design. Proficiency in data visualization and interpretation of ML results. Job responsibilities Proven experience as an MLOps Engineer or in a similar role, with an excellent understanding of AI/ML lifecycle management. Strong experience deploying and productionising ML models. Familiarity with data engineering concepts, including data … pipelines, ETL processes, and big data technologies. Excellent problem-solving skills and the ability to troubleshoot complex issues in AI/ML systems. Technical Insight Skills with MLOps concepts and principles. Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization tools (e.g., Docker, Kubernetes). Proficiency in programming languages such as Python, experience with AI/ML frameworks More ❯

We are looking for a highly skilled and experienced Senior MLOps Engineer to join our team. This role will be involved in designing, implementing, and maintaining robust and scalable machine learning pipelines. This person will possess a strong background in DevOps practices, machine learning principles, and cloud computing platforms. You will work closely with data scientists and software engineers to … tune ML models for performance and accuracy. • Understanding of statistical analysis and experimental design. • Proficiency in data visualization and interpretation of ML results. Job Responsibilities • Proven experience as an MLOps Engineer or in a similar role, with an excellent understanding of AI/ML lifecycle management. • Strong experience deploying and productionizing ML models. • Familiarity with data engineering concepts, including data … pipelines, ETL processes, and big data technologies. • Excellent problem-solving skills and the ability to troubleshoot complex issues in AI/ML systems. Technical Insight • Skills with MLOps concepts and principles. • Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization tools (e.g., Docker, Kubernetes). • Proficiency in programming languages such as Python, experience with AI/ML frameworks More ❯

Azure , GCP ). Experience deploying ML models or managing AI/ML workflows in production. Working knowledge of big data technologies like Spark , Hive , or Hadoop . Familiarity with MLOps tools (e.g., MLflow , Kubeflow , DataRobot ). Education Bachelor’s degree in Computer Science , Software Engineering , or a related technical field — or equivalent practical experience. Why Join Us Work on cutting More ❯

Azure , GCP ). Experience deploying ML models or managing AI/ML workflows in production. Working knowledge of big data technologies like Spark , Hive , or Hadoop . Familiarity with MLOps tools (e.g., MLflow , Kubeflow , DataRobot ). Education Bachelor’s degree in Computer Science , Software Engineering , or a related technical field — or equivalent practical experience. Why Join Us Work on cutting More ❯

and observability-either independently or in collaboration with other specialists. Optimize model pipelines for latency, scalability, and cost-efficiency , and support real-time and batch inference needs. Collaborate with MLOps, DevOps, and data engineering teams to ensure reliable model deployment and system integration. Stay informed on current research and emerging tools in LLMs, generative AI, and autonomous agents , and evaluate More ❯

in Python Excellent communication skills Preferred Qualifications & Skills: If you have the following characteristics, it would be a plus: Master's or PhD in Computer Science Some experience with MLOps would be very beneficial. Experience with building search applications using Azure Search, Sinequa, Elastic or anything Lucene-based would come in handy but is not necessary. Familiarity with Azure cloud More ❯

positive change and use AI for good. We are growing our team of engineers to help deliver an increasing number of client projects. You won't need an existing MLOps background to apply for this role. You'll learn as you go by immersing yourself in this exciting new field. What we're looking for We've seen considerable growth … over the past few years and this will continue as we build on our reputation as Open Source MLOps experts, while working with the community, and delivering solutions to our clients. The ideal candidate would be motivated to grow and progress in line with the company's ambitions. As well as being a great engineer, motivated by the chance to … be at the forefront of MLOps adoption, you'll also enjoy being part of a culture that values: Loving what we do: a real passion for Open Source, MLOps and taking pride in great work. Just trying it: MLOps is an exciting new field. We love to develop new skills, solve new problems and thrive on a challenge. Being greater More ❯

as clustering, classification, regression, and anomaly detection to discover patterns and trends in large datasets. Analyze and preprocess large datasets to extract meaningful insights and features for model training MLOps - Deployment into production environments, Monitoring and Maintenance Experience deploying and maintaining large-scale ML inference pipelines into production Implement and monitor model performance in production environments on Kubernetes and AWS … Proficiency in Python and SQL. Experience with big data technologies like Apache Hadoop and Apache Spark. Familiarity with real-time data processing frameworks such as Apache Kafka or Flink. MLOps & Deployment: Experience deploying and maintaining large-scale ML inference pipelines into production environments. Proficiency with Docker for containerization and Kubernetes for orchestration. Familiarity with AWS cloud platform (experience with GCP More ❯

measurement. Collaborative Development: Work closely with marketing strategists, data analysts, data engineers, and product owners to define use cases and deliver scalable solutions. Model Deployment & Monitoring: Deploy models using MLOps practices and tools (e.g., MLflow, Airflow, Docker, cloud platforms) ensuring performance, reliability, and governance compliance. Innovation & Research: Stay current on advancements in AI/ML and proactively bring forward new More ❯

measurement. Collaborative Development: Work closely with marketing strategists, data analysts, data engineers, and product owners to define use cases and deliver scalable solutions. Model Deployment & Monitoring: Deploy models using MLOps practices and tools (e.g., MLflow, Airflow, Docker, cloud platforms) ensuring performance, reliability, and governance compliance. Innovation & Research: Stay current on advancements in AI/ML and proactively bring forward new More ❯

release cycles Strong understanding of data science, machine learning concepts, and analytics capabilities Experience with AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, etc.) Experience with MLOps practices (e.g., model deployment, monitoring, retraining workflows) for operationalizing machine learning models effectively Excellent communication skills with the ability to translate complex technical concepts for different audiences Proven track record More ❯

release cycles Strong understanding of data science, machine learning concepts, and analytics capabilities Experience with AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, etc.) Experience with MLOps practices (e.g., model deployment, monitoring, retraining workflows) for operationalizing machine learning models effectively Excellent communication skills with the ability to translate complex technical concepts for different audiences Proven track record More ❯

ML deployment, you will have the responsibility of managing projects with autonomy across the full data lifecycle. Responsibilities📝 As an ML Engineer at Un:hurd music, you'll be: MLOps and Model Deployment : Own the deployment, maintenance, and retraining of machine learning models in production environments, designing scalable system architectures to ensure performance and resilience. Data Collection and Integration : Develop More ❯

ML deployment, you will have the responsibility of managing projects with autonomy across the full data lifecycle. Responsibilities📝 As an ML Engineer at Un:hurd music, you'll be: MLOps and Model Deployment : Own the deployment, maintenance, and retraining of machine learning models in production environments, designing scalable system architectures to ensure performance and resilience. Data Collection and Integration : Develop More ❯

ML deployment, you will have the responsibility of managing projects with autonomy across the full data lifecycle. Responsibilities As an ML Engineer at Un:hurd music, you'll be: MLOps and Model Deployment : Own the deployment, maintenance, and retraining of machine learning models in production environments, designing scalable system architectures to ensure performance and resilience. Data Collection and Integration : Develop More ❯

Job Description - Senior Manager - Machine Learning Engineering (006207) Our purpose is to make great financial decision making a breeze for everyone, and that purpose drives us every day. It's why we're on a mission to create an automated More ❯

production. We work closely with stakeholders across the business to expand the understanding and impact of machine learning and AI throughout Trainline. The Role We are looking for a MLOps Engineering Manager to join our team and help shape the future of train travel. You will be part of a highly innovative AI and ML team working alongside engineers, scientists … have the opportunity to work with fellow ML enthusiasts on large-scale production systems, delivering highly impactful products that make a difference to our millions of users. As a MLOps Engineering Manager at Trainline you will Build a new team of MLOps Engineers working alongside ML Engineers, Data Engineers, Software Engineers, Data Scientists and Product Managers Define MLOps processes and … modelling and evaluation techniques. Have experience with Cloud infrastructure (ideally AWS), DevOps technologies such as Docker or Terraform and CI/CD processes and tools. Have previously worked with MLOps tools like MLFlow and Airflow, or on common problems such as model and API monitoring, data drift and validation, autoscaling, access permissions Have previously worked with monitoring tools such as More ❯

Press Tab to Move to Skip to Content Link Job Title: Principal MLOps/GenAI Infrastructure Engineer Salary: £76,700 - 87,600 (The expected salary range for this role reflects internal benchmarking and external market insights.) Band: D Location: London/Salford/Glasgow/Newcastle/Cardiff (Candidates will be considered for either location. This is a hybrid role … and do the best work of their careers. Your Key Responsibilities And Impact Lead the design, development, and evolution of robust tooling and platforms to support scalable Data Science, MLOps, and LLMOps workflows across the organisation. Drive strategy and execution for deploying, serving, and monitoring large language models (LLMs) in real-time and batch environments using Amazon SageMaker, Bedrock, and … culture through mentorship, knowledge sharing, and thought leadership via deep dives, brown bags, internal tech talks, and cross-team collaboration. Your Skills And Experience Extensive experience in DevOps/MLOps roles with demonstrated impact in building, scaling, and securing ML/AI infrastructure in cloud-native environments. Strong experience with AWS services such as SageMaker, Bedrock, S3, EC2, Lambda, IAM More ❯

Press Tab to Move to Skip to Content Link Job Title: Principal MLOps/GenAI Infrastructure Engineer Salary: £76,700 - 87,600 (The expected salary range for this role reflects internal benchmarking and external market insights.) Band: D Location: London/Salford/Glasgow/Newcastle/Cardiff (Candidates will be considered for either location. This is a hybrid role … and do the best work of their careers. Your Key Responsibilities And Impact Lead the design, development, and evolution of robust tooling and platforms to support scalable Data Science, MLOps, and LLMOps workflows across the organisation. Drive strategy and execution for deploying, serving, and monitoring large language models (LLMs) in real-time and batch environments using Amazon SageMaker, Bedrock, and … culture through mentorship, knowledge sharing, and thought leadership via deep dives, brown bags, internal tech talks, and cross-team collaboration. Your Skills And Experience Extensive experience in DevOps/MLOps roles with demonstrated impact in building, scaling, and securing ML/AI infrastructure in cloud-native environments. Strong experience with AWS services such as SageMaker, Bedrock, S3, EC2, Lambda, IAM More ❯

Press Tab to Move to Skip to Content Link Job Title: Principal MLOps/GenAI Infrastructure Engineer Salary: £76,700 - 87,600 (The expected salary range for this role reflects internal benchmarking and external market insights.) Band: D Location: London/Salford/Glasgow/Newcastle/Cardiff (Candidates will be considered for either location. This is a hybrid role … and do the best work of their careers. Your Key Responsibilities And Impact Lead the design, development, and evolution of robust tooling and platforms to support scalable Data Science, MLOps, and LLMOps workflows across the organisation. Drive strategy and execution for deploying, serving, and monitoring large language models (LLMs) in real-time and batch environments using Amazon SageMaker, Bedrock, and … culture through mentorship, knowledge sharing, and thought leadership via deep dives, brown bags, internal tech talks, and cross-team collaboration. Your Skills And Experience Extensive experience in DevOps/MLOps roles with demonstrated impact in building, scaling, and securing ML/AI infrastructure in cloud-native environments. Strong experience with AWS services such as SageMaker, Bedrock, S3, EC2, Lambda, IAM 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 ❯

We are partnering with a prestigious investment bank to find a highly skilled and Hands-on Machine Learning Operations (MLOps) Lead. This role will be pivotal in building out a greenfield framework for the deployment and management of scalable AI/ML solutions, specifically for the front and Middle Office user base. The role is to define and set up … a greenfield standardized MLOps framework for capital markets and set up all the tools and best practices to educate data scientists and equip them with the right tools and expertise. You MUST be hands on. A strong understanding of Devops, Machine learning and Data engineering is required to enable to right candidate to implement the MLOps processes. This team are … areas and business stakeholders, so relationship building and good communication will be key. You will bring a expertise in data science or data engineering, with a specific focus on MLOps for at least 2 years . This platform is critical and will be rolled out across the bank, so we are looking for only the highest calibre candidates with experience More ❯

in structured data querying and other business-specific applications Integrate LLMs with structured data systems (e.g., SQL databases, BigQuery, GCS) to enable natural language querying and advanced analytics. Implementing MLOps/LLMOps pipelines for deploying LLMs in production, monitoring their performance, and ensuring scalability. Evaluating LLM performance, optimising hyperparameters, and ensuring alignment with business objectives. Develop and maintain data integration … LangGraph, including prompt engineering, fine-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. MLOps/LLMOps 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 More ❯

testing, validation, deployment, to monitoring and retraining of models within different environments. If you've a strong understanding of Microsoft Azure, fluency in data science coding, and expertise in MLOps frameworks, we want to hear from you. Bring your excellent communication, problem-solving, and organizational skills to our team and help us drive innovation and excellence. This is a flexible … Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc You'll be skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management and organisation skills Ability to diagnose and troubleshoot problems quickly Excellent problem-solving and analytic … services, Event Hubs, Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc. Skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management and organisation skills Ability to diagnose and troubleshoot problems quickly Excellent problem-solving and analytic More ❯

testing, validation, deployment, to monitoring and retraining of models within different environments. If you've a strong understanding of Microsoft Azure, fluency in data science coding, and expertise in MLOps frameworks, we want to hear from you. Bring your excellent communication, problem-solving, and organizational skills to our team and help us drive innovation and excellence. This is a flexible … Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc You'll be skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management and organisation skills Ability to diagnose and troubleshoot problems quickly Excellent problem-solving and analytic … services, Event Hubs, Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc. Skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management and organisation skills Ability to diagnose and troubleshoot problems quickly Excellent problem-solving and analytic More ❯