226 to 250 of 291 MLOps Jobs in London

Job Title : Product Manager - MLOps Platform (AdTech Focus) Location : Remote (UK BASED) Salary/Rate : £550 Inside IR35 Start Date : 18/08/25 - 31/12/25 Job Type : Contract MUST BE ELIGIBLE FOR BPSS About the Client: Our client is a global leader in the digital advertising space, driving innovation across programmatic media, data platforms, and … real-time analytics. They are embarking on a strategic initiative to build a greenfield MLOps platform to power advanced machine learning use cases across their AdTech ecosystem. This is a fully remote role, inside IR35, offering the chance to own and shape foundational ML infrastructure at scale. Key Responsibilities: Define and own the product vision and roadmap for a brand … new MLOps platform, built from the ground up to support scalable, secure, and efficient ML model development, deployment, and monitoring. Work closely with data science, engineering, analytics, and AdOps teams to understand current workflows and identify opportunities to streamline and automate the ML lifecycle. Assess existing data, analytics, and infrastructure frameworks to identify reusable components and define the architectural blueprint More ❯

part of multi-disciplinary teams. Youll work in a fast moving, agile environment and will be involved in implementing machine learning algorithms, building production Machine Learning systems and developing MLOps processes. Youll help deliver some of the most exciting digital programmes around for clients in a range of industries by: Applying cross-disciplinary thinking Building a deep understanding of business … libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow), with a preference for PySpark experience Model Productionisation: Experience in taking Machine Learning models from development to production CI/CD and MLOps Experience : Familiarity with Continuous Integration and Continuous Deployment pipelines, especially in a Machine Learning or DevOps context Cloud Platforms : Experience building solutions using major cloud services (Azure, AWS, GCP) Analytical More ❯

client requirements into scalable, cloud-based AI architectures that address both technical feasibility and business impact. Propose end-to-end AI/ML solutions—including model design, data pipelines, MLOps, and platform integration—tailored to each opportunity. 3. Support Sales and Bid Activity Lead the technical response for AI-related RFPs, RFIs, and proposals, including solution overviews, technical narratives, architecture … them with AI/ML solutions in cloud environments (Azure, AWS, or GCP). Deep technical understanding of AI/ML concepts: supervised and unsupervised learning, GenAI, LLMs, embeddings, MLOps, vector search. Experience designing solutions using tools such as Azure ML, AWS SageMaker, Google Vertex AI, Databricks, LangChain, and Hugging Face. Ability to develop architecture artefacts (e.g., HLDs), estimate effort More ❯

tune and optimize pre-trained large language models and multi-modal models for targeted use cases, ensuring high performance and low latency in production. Implement distributed training and scalable MLOps pipelines for continuous model improvement Collaborate with cross-functional teams-research, product, and engineering-to embed AI capabilities into products and services Evaluate and select appropriate AI frameworks (e.g., LangChain … structured and unstructured data; ability to integrate these processes into scalable pipelines Experience deploying AI models and full-stack applications using cloud-native tools Strong grasp of DevOp/MLOps best practices, including version control and CI/CD Excellent problem-solving, debugging and rapid prototyping Strong project management skills to coordinate effectively with technical and business teams Demonstrated understanding More ❯

Opens in a new window Opens an external website Opens an external website in a new window Join the InstaDeep journey Innovation is at the heart of what we do. We work as a cohesive team that collectively develops real More ❯

The driving force behind our Machine Learning and Data Science infrastructure at Mimecast Embrace the incredible opportunities that lie within Mimecast, where innovation and impact converge. The cybersecurity industry is experiencing exponential growth, and by joining us, you'll be More ❯

My client, a global fintech company disrupting the world of embedded finance, is seeking a MLOps Engineer to join their team. It is a hybrid role and you will need to be in their London office 3 days per week (Tuesday to Thursday). Regarding daily rate, flexibility is on offer, and the company is still determining whether this is More ❯

Solutions Architect - DevOps/DevSecOps/MLOps Solutions Architect UNITED KINGDOM Solutions Architect - DevOps/DevSecOps/MLOps - LONDON - UNITED KINGDOM Salary: £ 160,000 (80/20 split) Remote Status: Hybrid - 3 days/week Job Description: Looking for a new pure-play Pre-Sales/Sales Engineer role at a market leader in DevOps, DevSecOps, and MLOps Well, this … Represent the company at industry events and conferences Train customers and community members on product capabilities Feed back frontline insights to shape the product roadmap Stay ahead of DevOps & MLOps trends and bring that expertise to every customer conversation This is not a back-office architect role. You'll be front and centre in the sales process - a trusted technical More ❯

excited by the challenge of applying data science at scale. You’ll work closely with cross-functional teams to operationalize models, support product development, and contribute to a modern MLOps pipeline. What You’ll Do Develop and deploy predictive models using behavioural and real-world data Translate complex datasets into actionable insights that improve healthcare outcomes Contribute to the full … and feature engineering to model deployment and monitoring Collaborate with engineering and product teams to ensure models are integrated into production systems via scalable pipelines Champion best practices in MLOps, including CI/CD for ML, model versioning, testing, and monitoring Design experiments (A/B testing, uplift modelling) to measure impact and optimize performance What We’re Looking For … behaviour data—ideally within healthcare, digital health, or related B2C environments Strong programming skills in Python, with experience using libraries like scikit-learn, XGBoost, and pandas Practical experience in MLOps or strong knowledge of model deployment (e.g. MLflow, Airflow, Docker, Kubernetes, model monitoring tools) Familiarity with cloud environments (AWS, GCP, or Azure) and data pipelines Excellent communication skills—able to More ❯

excited by the challenge of applying data science at scale. You’ll work closely with cross-functional teams to operationalize models, support product development, and contribute to a modern MLOps pipeline. What You’ll Do Develop and deploy predictive models using behavioural and real-world data Translate complex datasets into actionable insights that improve healthcare outcomes Contribute to the full … and feature engineering to model deployment and monitoring Collaborate with engineering and product teams to ensure models are integrated into production systems via scalable pipelines Champion best practices in MLOps, including CI/CD for ML, model versioning, testing, and monitoring Design experiments (A/B testing, uplift modelling) to measure impact and optimize performance What We’re Looking For … behaviour data—ideally within healthcare, digital health, or related B2C environments Strong programming skills in Python, with experience using libraries like scikit-learn, XGBoost, and pandas Practical experience in MLOps or strong knowledge of model deployment (e.g. MLflow, Airflow, Docker, Kubernetes, model monitoring tools) Familiarity with cloud environments (AWS, GCP, or Azure) and data pipelines Excellent communication skills—able to More ❯

maintaining an organization's data architecture and strategy, ensuring that data is collected, stored, and processed efficiently and securely to support business intelligence, data analytics, and machine learning operations (MLOps) practices. Key Responsibilities Designing Data Architecture: Plan and implement a robust, scalable data architecture that integrates data from various sources and supports diverse analytical needs, while optimizing costs and meeting … ensuring data quality and consistency. Enabling Data Intelligence and Analytics: Build and maintain data warehouses, data marts, and data lakes to support business intelligence and data analytics initiatives. Supporting MLOps Practices: Collaborate with data scientists and machine learning engineers to design and implement data infrastructure and processes that support machine learning model development, deployment, and maintenance. Ensuring Data Security and … understand data requirements and translate them into technical solutions. Staying Abreast of Technological Advancements: Keep up-to-date with emerging technologies and trends in data architecture, data engineering, and MLOps to identify opportunities for improvement and innovation. Optimizing Data Performance: Monitor and analyze data processing performance, identify bottlenecks, and implement optimizations to enhance efficiency and scalability. Documentation and Knowledge Sharing More ❯

big data workflows Utilize Azure Cloud services (Data Lake, Functions, App Services) for development and deployment Implement and maintain containerized solutions using Docker and CI/CD pipelines Apply MLOps practices using tools like MLFlow , Git-based versioning, and environment tracking Build and integrate AI and intelligent automation frameworks Ensure applications meet performance, reliability, and scalability requirements Required Skills & Experience … Databricks or Microsoft Fabric Proficiency in Azure cloud services including Data Lake, Functions, and App Services Strong understanding of Docker , CI/CD workflows, and automation pipelines Familiarity with MLOps tooling such as MLFlow, Git version control, and environment management Desirable Skills & Interests: Experience with frameworks like LangChain , Langflow , or similar tools for building AI agents Understanding of Large Language More ❯

enable the building and maintenance of our AI systems. Our teams make extensive use of open source technologies such as, Kubernetes, Kubeflow, KServe, Argo, Buildpacks, and other cloud-native MLOps technologies. From technical governance to upstream collaboration, we are committed to enhancing the impact and sustainability of open source. Join the AI Group as a Senior ML Platform Engineer and … workflows, pinpoint, and resolve inefficiencies, and to inform the next set of features for the platforms Collaborate with open-source communities and AI application teams to build a cohesive MLOps experience Design CI/CD automation frameworks that incorporate regulatory requirements Develop cloud-native deployment patterns for AI systems across environments Troubleshoot and debug user issues Provide operational and user More ❯

Job description At Permutable AI, were building intelligent systems to automate market analysis using advanced NLP and multi-LLM frameworks. Our goal is to dramatically accelerate how financial information is processed, understood, and acted on, enabling faster, smarter decisions for More ❯

Our Company: QiH is a fast-growing, innovative, and progressive scale-up business headquartered in London with a collective of brilliant brains in Skopje. We are at the start of an exciting journey as we build out our internal engineering More ❯

Our Company: QiH is a fast-growing, innovative, and progressive scale-up business headquartered in London with a collective of brilliant brains in Skopje. We are at the start of an exciting journey as we build out our internal engineering More ❯

extensive geospatial information. You will take ownership not only of modeling and metric development but also of the end-to-end ML lifecycle, including deployment and monitoring using modern MLOps frameworks. Collaboration with data engineers and cross-functional teams is essential, as you’ll help shape the ML strategy and drive innovation in how healthcare behaviors are understood and acted … Strong Python skills and experience with Databricks or similar platforms Proven track record in predictive modelling with messy, real-world datasets (survey, geospatial, or similar) Hands-on experience with MLOps tools and practices (e.g., MLFlow) and deploying models in cloud environments (GCP, AWS, or Azure) Proactive, creative problem solver with a startup mindset and strong communication skills Comfortable taking technical More ❯

extensive geospatial information. You will take ownership not only of modeling and metric development but also of the end-to-end ML lifecycle, including deployment and monitoring using modern MLOps frameworks. Collaboration with data engineers and cross-functional teams is essential, as you’ll help shape the ML strategy and drive innovation in how healthcare behaviors are understood and acted … Strong Python skills and experience with Databricks or similar platforms Proven track record in predictive modelling with messy, real-world datasets (survey, geospatial, or similar) Hands-on experience with MLOps tools and practices (e.g., MLFlow) and deploying models in cloud environments (GCP, AWS, or Azure) Proactive, creative problem solver with a startup mindset and strong communication skills Comfortable taking technical More ❯

will be based on your skills and experience talk with your recruiter to learn more. Base pay range Direct message the job poster from Explore Group Were hiring an MLOps Engineer to create and maintain the systems that keep advanced AI models running smoothly at scale. In this role, youll work alongside data science and engineering teams to design production … application architectures, working closely with product and engineering. Drive continuous improvement across the ML lifecycle, from A/B testing to incident response. What Youll Bring 3+ years in MLOps, DevOps, or software engineering focused on ML systems. Familiarity with LLM deployment and operational support. Experience with Docker, Kubernetes, and cloud ML services. Understanding of vector databases and search optimisation More ❯

roadmap and lead the development of AI-first features Productionize ML models, ensuring scalability, performance, and observability Design the infrastructure for deploying and maintaining ML systems in production (e.g., MLOps, CI/CD for ML, model versioning) Build systems that integrate AI into key parts of our stack, such as: Forecasting customer demand and renewable generation Dynamic pricing and energy … prioritize for both experimentation and reliability Bonus Familiarity with optimization, time series modeling, or forecasting Experience with large language models (LLMs), RAG, or generative AI in production Background in MLOps or AI infrastructure at scale Competitive salary and a stock options sign-on bonus Biannual bonus scheme Fully expensed tech to match your needs! Paid annual leave Breakfast and dinner More ❯

roadmap and lead the development of AI-first features Productionize ML models, ensuring scalability, performance, and observability Design the infrastructure for deploying and maintaining ML systems in production (e.g., MLOps, CI/CD for ML, model versioning) Build systems that integrate AI into key parts of our stack, such as: Forecasting customer demand and renewable generation Dynamic pricing and energy … prioritize for both experimentation and reliability Bonus Familiarity with optimization, time series modeling, or forecasting Experience with large language models (LLMs), RAG, or generative AI in production Background in MLOps or AI infrastructure at scale Competitive salary and a stock options sign-on bonus Biannual bonus scheme Fully expensed tech to match your needs! Paid annual leave Breakfast and dinner More ❯

Role Depop is looking for a dedicated Machine Learning Engineer to join our new Core ML team in the UK. You will work alongside ML Scientists, Backend Engineers, and MLOps to build, deploy, maintain, and monitor machine learning infrastructure, such as product matching pipelines, image embedding services, and lightweight classifier deployments, that support multiple product and marketing use cases across … and product teams across Depop to define integration requirements and coordinate deployments of shared ML components Help design and extend the ML platform at Depop in collaboration with the MLOps team, across areas such as: Robust prototyping and training workflows CI/CD for model deployment Real-time and batch model serving Online/offline feature consistency via our feature … ability to work independently Excellent communication skills across technical and non-technical stakeholders Experience designing systems in modern cloud environments (e.g. AWS, GCP) Technologies and Tools Python ML and MLOps tooling (e.g. SageMaker, Databricks, TFServing, MLflow) Common ML libraries (e.g. scikit-learn, PyTorch, TensorFlow) Spark and Databricks AWS services (e.g. IAM, S3, Redis, ECS) Shell scripting and related developer tooling More ❯

Unitary's future. Take ownership of customer outcomes with the autonomy to make decisions that surprise and delight our customers. Contribute full-stack development including software engineering, DevOps, and MLOps, along with light task and project management to ensure your AI solutions deliver maximum value. You We are looking for someone who is as excited about Unitary's mission as … better, but not essential, if you have: Experience working in a fully remote, international team Previous startup experience A background in building and operating agentic AI systems Experience with MLOps practices and tools, and monitoring machine learning systems in production Knowledge of CI/CD practices and tools such as GitLab CI, Argo CD Proficiency with SQL and NoSQL databases More ❯

Unitary's future. Take ownership of customer outcomes with the autonomy to make decisions that surprise and delight our customers. Contribute full-stack development including software engineering, DevOps, and MLOps, along with light task and project management to ensure your AI solutions deliver maximum value. Requirements You We are looking for someone who is as excited about Unitary's mission … better, but not essential, if you have: Experience working in a fully remote, international team Previous startup experience A background in building and operating agentic AI systems Experience with MLOps practices and tools, and monitoring machine learning systems in production Knowledge of CI/CD practices and tools such as GitLab CI, Argo CD Proficiency with SQL and NoSQL databases More ❯

Updraft. Helping you make changes that pay off. Updraft is an award winning, FCA-authorised, high-growth fintech based in London. Our vision is to revolutionise the way people spend and think about money, by automating the day to day More ❯