1 to 25 of 36 MLOps Jobs in England with Remote Work Options

results. Ability to apply ML solutions across various industries. Experience in full lifecycle model development, including compliance and security. Cloud-based ML deployment and MLOps expertise. Benefits: 26 days PTO + bank holidays Employee equity more »

My client, a Software Development Consultancy, are looking for an Azure Machine Learning Engineer with Active SC Clearance for an initial 6 month engagement. Key Skills Required: Excellent knowledge of Azure technologies for Machine Learning and AI Solid understanding of more »

to optimize infrastructure costs, increase operational efficiency, and enhance overall reliability and performance. Stay updated on emerging technologies and best practices in DevOps and MLOps to recommend and implement innovative solutions. KEY REQUIREMENTS: Proven experience building and automating cloud systems (DevOps Engineer, Site Reliability Engineer), preferably on AWS. Hands-on more »

Lead Data Scientist - London - Hybrid working 2 days a week in office. About the Business : At Cirium, our goal is to keep the world connected. We are the industry leader in aviation analytics; helping our customers understand the past, present more »

Senior Product Manager (Data/AI/ML) Location: London or Midlands - Remote Working Salary: £80,000 - £90,000 (plus benefits and bonus target of 20%) We are partnered with a market-leading sports streaming business, whose platforms are visited more »

part of a team PREFERRED BUT NOT REQUIRED: Experience with Spark or dbt Experience in deploying production systems on multiple cloud platforms Familiar with MLOps principles and practices in a production setting COMPENSATION/BENEFITS: Competitive salary + equity 30 days annual leave + UK bank holidays Learning Budget of more »

learning algorithms. Ability to apply data science principles commercially. Desirable Experience using R. Experience in Azure or AWS. Experience working in a Dev/MLOps environment. Understanding of Generative AI frameworks. Experience using any ML services. Experience using Git, SQL, PowerBI, or Tableau. Experience using Docker and Kubernetes. Experience working more »

machine learning and data science, such as Azure, OpenAI, Hugging Face, AWS ML/AI. Machine Learning Applications development life cycle processes and tools - MLOps, including building ETL data pipelines. Cutting-edge approaches to Machine Learning, including transformer models, diffusion models, and adversarial machine learning. Experience in fine-tuning off more »

London Permanentup to 90,000 Senior Product Manager (Data/AI/ML)Location: London or Midlands – Remote Working Salary: 80,000 – 90,000 (plus benefits and bonus target of 20%) We are partnered with a market-leading sports streaming more »

to develop advanced ML models and algorithms that power our data-driven solutions. To further strengthen our ML capabilities and streamline our ML operations (MLOps), we are seeking a skilled and motivated Platform Engineer to join our data science team. Role Overview As a Platform Engineer at Allianz Commercial, you … data scientists and data engineers to provision infrastructure and operationalize ML models and ensure their scalability, reliability, and performance. Your expertise in DevOps/MLOps and experience with the Azure cloud environment will be essential in designing and implementing end-to-end ML solutions. You will collaborate with cross-functional … production. This role requires strong technical skills, a solid understanding of Azure Cloud services and deployment/configuration processes, and experience with DevOps/MLOps best practices. Responsibilities Collaborate with data scientists and data engineers to understand ML requirements, and design and develop ML pipelines for data pre-processing, model more »

tasks. Conduct thorough exploratory data analysis to gain insights into text data characteristics and develop effective pre-processing strategies. Collaborate with data engineers and MLops Engineers to integrate NLP models into our data pipelines and systems. Evaluate and benchmark different NLP algorithms, knowledge graph frameworks, and LLM architectures, and recommend … reports, visualizations, and presentations. Collaborate with cross-functional teams to define project goals, requirements, and success metrics. Engage in collaborative efforts with Enterprise Architects, MLOps Engineers to trial use cases and deliberate on architectural configurations. Mentor and provide guidance to junior team members, fostering their growth and development in NLP. more »

We're looking for a Lead Machine Learning Engineer join our Data Engineering team. As the Lead ML Ops Engineer, you will be at the forefront of innovation, leading a small team of skilled engineers to develop and deploy scalable more »

LLMs for NLP tasks in industry Experience in Biomedical data or computational sciences Experience in cloud platforms such as GCP or AWS Experience with MLOps/LLMOps frameworks and best practices Competitive compensation package Private medical insurance (underwritten on a medical health disregarded basis) Life insurance (4 x salary) Individual more »

with one or more of the following packages: HuggingFace, Fastai, scikit-learn, XGBoost, LightGBM, Ray, any of the GenAI frameworks Experience with data engineering, MLOps and tools such as Docker and Kubernetes Experience with data pipeline tools Experience as an ML educator and/or building and executing customer training more »

with one or more of the following packages: HuggingFace, Fastai, scikit-learn, XGBoost, LightGBM, Ray Experience with hyperparameter optimization solutions Experience with data engineering, MLOps and tools such as Docker and Kubernetes Experience with data pipeline tools Experience as an ML educator and/or building and executing customer training more »

options, generous paid leave, and trips abroad #WhatWillYouBuild Why We Need This Role We are looking for a Technical Lead profile to manage the MLOps unit within the Intelligent Systems Group. The unit is currently horizontal, it includes both Platform and Machine Learning engineers and it is responsible for supporting … data scientists in deploying, maintaining and monitoring an increasing number of Python-based microservices, ETL pipelines, SaaS models, databases and vector stores. The MLOps Lead would need to act as an interface between data scientists, the data & analytics team and the platform engineering team. We need this role to keep … on development, deployments, monitoring and maintenance from the Intelligent Systems team. The role is needed to effectively plan and execute the roadmap for the MLOps team accounting for data science and product stakeholders, infrastructure and cost constraints. Support the definition of service architectures for new services while continuously working towards more »

machine learning and data science, such as Azure, OpenAI, Hugging Face, AWS ML/AI. Machine Learning Applications development life cycle processes and tools - MLOps, including building ETL data pipelines. Cutting-edge approaches to Machine Learning, including transformer models, diffusion models, and adversarial machine learning. Experience in fine-tuning off more »

culture where employees can bring their authentic selves to work. Key responsibilities of the role are summarised below: We are seeking an experienced Hybrid MLOps, DevOps, Dev Engineer to lead multiple projects while providing high-level strategic guidance to our clients. This role requires exceptional client-facing skills and the … ability to handle multiple projects simultaneously. The successful candidate will be responsible for working closely with a DevOps team of 4 and 2 MLOps engineers, advising clients on their strategic goals, and assisting them in delivery. Responsibilities: Implementation of DevOps best practices Working knowledge of Istio, Argo CD, Argo Workflows more »

environments. Proficiency or experience with Apache Spark. Familiarity or background in working with Azure. Experience orchestrating workflows, particularly within distributed system environments. Knowledge of MLOps principles and practices, especially in implementing them within production settings. Why Monolith? Our culture is passionate, engaging and collaborative. We are genuine, we bring our more »

and requirements for deploying their work into production. Develop and enhance mechanisms and processes to streamline the integration of causal AI models into the MLOps workflow, customizing it to suit causality. Design and implement tools, visualizations, and mechanisms that empower data scientists to deploy their work into production autonomously, reducing … dependencies on additional teams or assistance. Work directly on integrating key elements of MLOps workflow with causal AI capabilities, ensuring robustness, scalability, and efficiency. Act as a subject matter expert on processes and best practices, providing guidance and support to data scientists on deployment and monitoring. Collaborate with cross-functional … significant exposure to deploying machine learning models into production. Strong proficiency in Python for both machine learning engineering and data science tasks. Experience with MLOps practices, including model deployment, monitoring, version control, and CI/CD pipelines. Proven experience in data pipelining, system architecture, and design for scalable and reliable more »

models (fraud detection, risk assessment) with a focus on NER. Leverage CI/CD & containers for seamless integration & scalability. Automate ML Workflows: Build robust MLOps pipelines to automate data ingestion, pre-processing, model training & serving for efficient NLP workflows. Champion NLP Expertise: Collaborate with data science teams, translate model requirements … of NLP models. We're Looking For: Proven experience building and deploying NLP models, strong grasp of statistics, ML techniques, and proficiency in Python. MLOps & Cloud Infrastructure: A strong understanding of CI/CD pipelines, containerisation technologies (Docker, Kubernetes), and cloud platforms (AWS, Azure, GCP). Degree in Computer Science more »

role: Architecting, building and maintaining ML processing pipelines/workflows in Python via technologies such as Spark, serverless functions, Airflow, MLflow, or other. Implement MLOps and related DevOps focused on creating ML workflows for deploying models for large scale inference and optimisations. Build Docker containers, in collaboration with Data Scientists … in large scale digital applications. Extensive experience with programming in Python, Jupyter notebooks, Spark, and Docker Professional experience of designing, building and managing bespoke MLOps in cloud environments, using tools such as SageMaker Processing, SageMaker Pipelines, Apache Airflow, and MLflow. Strong, fundamental technical expertise in cloud-native technologies, such as more »

re seeking talented individuals to drive our mission forward to deliver industry-leading machine learning deployment and continue to make our mark in the MLOps space. We have created a culture that we re proud of driven by our passionate, talented team and our open, collaborative ethos. We operate on … with MLOps. About the role Help realise the product vision: Production-ready machine learning models within moments, not months. Our products make enterprise-grade MLOps easy. Help design, build and extend Seldon's core product range of MLOps (Machine learning operations) tools and products. Help enterprises deploy their machine learning … models at scale across a wide range of use-cases and sectors. Extend the state of the art in the developing area of MLOps including: Managing the production lifecycle of ML models from initial deployment, to testing and updating of the next iteration. Essential skills A degree or higher level more »

become an integral part of a growing company at the forefront of of cutting edge technology. Key Responsibilities: You'll be developing out their MLOps system all greenfield projects. Lead the development and deployment of end-to-end Ops pipelines supporting the entire ML lifecycle. Drive initiatives for CI/… work effectively to multiple internal teams including the data science and engineering teams. Grow team to 5 within 12 months Experience Required: Experience building MLOps systems from scratch Open to industry Package: Up to £105,000 Hybrid working – office based in London Industry leading benefits How to Apply: If you more »

to become an integral part ofa growing company at the forefront of of cutting edge technology. Key Responsibilities: You'll be developing out their MLOps system all greenfieldprojects. Lead the development and deployment of end-to-endOps pipelines supporting the entire ML lifecycle. Be the main point of contact, presenting … technical workeffectively to multiple internal teams including the data science andengineering teams. Grow team to 5 within 12 months Experience Required: Experience building MLOps systems from scratch Open to industry Package: Up to £105,000 Hybrid working office based inLondon Industry leading benefits How to Apply: If you re more »