1 to 25 of 163 Remote MLOps Jobs in England

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 ❯

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 ❯

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 ❯

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 ❯

You will collaborate with a team of experts to solve complex business challenges using cutting-edge AI technologies. KEY RESPONSIBILITIES Design and architect scalable ML solutions using statistical modeling, MLOps frameworks and cloud technologies Build machine learning models for marketing attribution, customer prediction, segmentation, and recommendation systems with deep understanding of customer experience and marketing use-cases Implement end-to … SQL skills and experience with data warehousing solutions (Snowflake, BigQuery, Redshift) Experience with cloud platforms (AWS, Azure, GCP) and their ML services (SageMaker, Azure ML, Vertex AI) Knowledge of MLOps tools including Docker, Kubernetes, MLflow, Kubeflow, or similar platforms Experience with version control (Git) and collaborative development practices Excellent analytical thinking and problem-solving abilities Strong communication skills with ability More ❯

cleaning and ML validation strategies. Scalable Solutions: Building training pipelines and components to ensure scalable ML solutions, address errors, and provide education to upskill teams working on ML, enhancing MLOps proficiency. We offer a flexible hybrid working model with 2 days from home and 2-3 days at our central London office, where you'll collaborate with digital specialists and 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 ❯

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 ❯

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 ❯

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 ❯