176 to 200 of 1,176 MLOps Jobs in the UK

for ML and deep learning (SparkML, Tensorflow, Keras). Demonstrated ability to work on multi-disciplinary teams with diverse skillsets. Deploying machine learning models and systems to production (DevOps, MLOps, CI/CD). Experience of working in cloud environments (Azure, GCP, AWS). You are also expected to have: Excellent leadership skills. Able to articulate complex data science concepts More ❯

to embed intelligent features into our platform. Ensure smooth end-to-end integration of AI/ML functionality within broader product development efforts. Technical Leadership Define best practices for MLOps, model deployment, and performance tuning. Evaluate and implement new frameworks, tools, and cloud-native AI solutions (including LLMs). Make strategic technical decisions that align with broader business goals. Support More ❯

to embed intelligent features into our platform. Ensure smooth end-to-end integration of AI/ML functionality within broader product development efforts. Technical Leadership Define best practices for MLOps, model deployment, and performance tuning. Evaluate and implement new frameworks, tools, and cloud-native AI solutions (including LLMs). Make strategic technical decisions that align with broader business goals. Support More ❯

to embed intelligent features into our platform. Ensure smooth end-to-end integration of AI/ML functionality within broader product development efforts. Technical Leadership Define best practices for MLOps, model deployment, and performance tuning. Evaluate and implement new frameworks, tools, and cloud-native AI solutions (including LLMs). Make strategic technical decisions that align with broader business goals. Support More ❯

Proven track record of deploying AI/ML applications in a production environment, with expertise in deploying models on AWS platforms such as SageMaker or Bedrock. Deep familiarity with MLOps practices, covering the full cycle from design, experimentation, deployment, to monitoring and maintenance of machine learning models. Expertise in machine learning frameworks such as TensorFlow, PyTorch, PyTorch Lightning, or Scikit More ❯

a customer facing role 2+ years’ experience in a data-driven role, with exposure to software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps) Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow) Distributed computing frameworks (e.g., Spark, Dask) Cloud platforms (e.g., AWS, Azure, GCP) and HP 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 ❯

a customer facing role 2+ years’ experience in a data-driven role, with exposure to software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps) Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow) Distributed computing frameworks (e.g., Spark, Dask) Cloud platforms (e.g., AWS, Azure, GCP) and HP More ❯

and dimensional modelling. Knowledge of integration patterns, ETL/ELT processes, and tools (e.g., Apache Airflow, Azure Data Factory, Informatica, Talend) to orchestrate data workflows. Familiarity with DevOps/MLOps principles, CI/CD pipelines, and infrastructure as code (e.g., Terraform, CloudFormation). Basic understanding of data security measures, encryption, IAM, and compliance (GDPR, CCPA); ability to evaluate potential vulnerabilities More ❯

building more effective autonomous agents for complex property management workflows and decision-making processes Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch), LLM orchestration tools (LangChain, LangGraph), MLOps practices and tooling (such as MLflow, Kubeflow, or similar), vector databases, and cloud platforms (AWS, Azure, GCP) with their AI/ML offerings Preferably hands-on experience with voice technologies More ❯

non-technical stakeholders, Demonstrated interest in building solutions - not just models - that solve real problems. Preferred Qualifications Experience working with LLMs, GenAI, or retrieval-augmented generation systems, Familiarity with MLOps, including Docker, CI/CD, or model deployment in cloud environments, Exposure to cloud platforms (Azure, GCP, AWS) and data tools such as MLflow, Airflow, Databricks, Previous consulting or client More ❯

non-technical stakeholders, Demonstrated interest in building solutions - not just models - that solve real problems. Preferred Qualifications Experience working with LLMs, GenAI, or retrieval-augmented generation systems, Familiarity with MLOps, including Docker, CI/CD, or model deployment in cloud environments, Exposure to cloud platforms (Azure, GCP, AWS) and data tools such as MLflow, Airflow, Databricks, Previous consulting or client More ❯

pipelines using AWS Lambda, Step Functions, and API Gateway for real-time AI inference and automation. Familiarity with containerized AI deployments using Amazon EKS and AWS Fargate. DevOps and MLOps Expertise: Hands-on experience with CI/CD pipelines for AI/ML workflows using AWS CodePipeline, CodeBuild, and SageMaker Pipelines. Proficiency in monitoring and maintaining AI systems with Amazon More ❯

advice and best practices to overcome these challenges and successfully deliver the expected business outcomes. Skills and experience required Experience in any related software/DevOps/DevSecOps/MLOps/AI roles within a regulated engineering environment. CI/CD deployment Software/AI development and deployment in complex programmes Strong Data and Application understanding with underpinning Infrastructure solution More ❯

when needed, as appropriate. Collaborate with other Computational Team's engineers to facilitate the deployment of the models within BH's workflows. This may include minor front-end and MLOps tasks. Write periodic reports to show progress and participate in team planning/review activities with both BH and BCU. Co-author papers and participate in conferences and dissemination activities More ❯

platforms such as OpenAI on Azure, AWS Bedrock, GCP Vertex AI, or Gemini AI. Architecture & Deployment: Designing, deploying, and scaling AI architectures aligned to enterprise standards. Proven experience in MLOps and AI lifecycle management, with scalable deployments across AWS, GCP, and Azure. Bridging business and technical teams, owning high- and low-level design for services, products, and solutions. Optimizing solutions More ❯

advice and best practices to overcome these challenges and successfully deliver the expected business outcomes. Skills and experience required Experience in any related software/DevOps/DevSecOps/MLOps/AI roles within a regulated engineering environment. CI/CD deployment Software/AI development and deployment in complex programmes Strong Data and Application understanding with underpinning Infrastructure solution More ❯

Senior Data Scientist - Creative Optimization Join to apply for the Senior Data Scientist - Creative Optimization role at GroupM Senior Data Scientist - Creative Optimization 1 day ago Be among the first 25 applicants Join to apply for the Senior Data Scientist More ❯

MLOps Engineer London£60,000-£70,000 About the Role: Join a cutting-edge technology company at the forefront of immersive experiences powered by machine learning and extended reality. We are seeking a skilled MLOps Engineer to help build, deploy, and maintain scalable machine learning infrastructure that drives innovation in our products. You will play a critical role in developing … scalable ML infrastructure that powers immersive XR applications with real-time 3D content. Key Responsibilities: Design, develop, and maintain scalable MLOps pipelines tailored for XR applications, ensuring smooth deployment and monitoring of machine learning models. Collaborate closely with 3D artists and XR developers to integrate machine learning workflows with 3D rendering engines. Optimize ML models and workflows for real-time … related to ML inference and 3D rendering workloads. Develop monitoring solutions to track model performance and system health in production. Stay up to date with the latest trends in MLOps, XR technologies, and 3D rendering techniques to propose innovative improvements. Qualifications: Proven experience as an MLOps engineer or similar role with a focus on 3D applications Strong programming skills in More ❯

Job Description Senior MLOps Engineer - Hybrid/Dundee Salary up to £70,000 We are looking for a Senior MLOps Engineer to join a Scottish company working on cutting edge AI solutions. You will play a pivotal role in ensuring that ML initiatives drive value effectively while maintaining operational excellence. The Role: Managing and optimising existing ML model deployments to …/CD pipelines, monitoring systems, and infrastructure automation. Upholding best practices in security, cost management, and infrastructure design for cloud environments. The Ideal Candidate: 4+ years of experience in MLOps, DevOps, or software engineering roles. Strong programming skills in Python and familiarity with ML frameworks. Extensive experience with AWS services (e.g., SageMaker, ECS, Lambda) and cloud environments. Proficiency with containerization More ❯

day ago Be among the first 25 applicants Salary up to £70,000 We are looking for a About Senior MLOps Engineer Hybrid/Dundee Salary up to £70,000 We are looking for a Senior MLOps Engineer to join a Scottish company working on cutting edge AI solutions. You will play a pivotal role in ensuring that ML initiatives More ❯

experiment, ship, and see your work reflected in customers' financial freedom. At Updraft, you'll help build a fairer credit system. The Role We're looking for an experienced MLOps Engineer for a 3-month contract to lead the development of our ML deployment, testing, monitoring, and feature engineering pipelines . You'll be responsible for establishing best practices and … learning workflows from training to deployment and beyond. The role could be extended to a longer DevOps contract. What You'll Do - Design and build an end-to-end MLOps pipeline using AWS , with a strong focus on SageMaker for training, deployment, and hosting. - Integrate and operationalize MLflow for model versioning, experiment tracking, and reproducibility. - Architect and implement a feature … workflows (training, evaluation, deployment), integrating with tools such as GitHub Actions , CodePipeline , or Jenkins . - Create internal documentation and onboarding guides for engineering and data teams to adopt new MLOps practices. What We're Looking For - 3+ years of experience in MLOps, DevOps, or ML infrastructure roles. - Deep familiarity with AWS services , especially SageMaker , S3, Lambda, CloudWatch, IAM, and optionally More ❯

changes. We welcome open-minded developers who like to share knowledge and help each other to push Optimove forward using the cutting edge of today's tech. The new MLOps team will be responsible for the seamless deployment, monitoring, and maintenance of machine learning models in production. Acting as the critical link between the data science and R&D teams … ML systems for performance, errors, and drift. Automate infrastructure provisioning and deployment using IaC tools. Collaborate with team leader to define technical strategies. Requirements : 4+ years of experience in MLOps, DevOps, or software engineering roles. Strong programming skills in Python and familiarity with ML frameworks. Extensive experience with AWS services (e.g., SageMaker, ECS, Lambda) and cloud environments. Proficiency with containerization More ❯

expertise and experience of Shallow ML frameworks - regression, classification, clustering; time series forecasting (prophet, ARIMA, SARIMA); dimensionality reduction approaches Proven experience in modern code development practices and implementation of MLOps strategies in the cloud to drive operational and infrastructure cost efficiencies. Knowledge of wider data warehousing, data architecture of data modelling concepts. Hands on experience designing, building, and maintaining ML … drive the adoption of best practice approaches to data science solution development, coaching, and supporting the wider data science team. Scope of Responsibility: Designing and developing our ML Operations (MLOps) infrastructure and practices to support the effective transition of machine learning models and PoCs into production. Working closely with business stakeholders to translate high-level business problems into the design … existing ML models post deployment. Designing, developing, and maintaining data science models and solutions, as well as explaining the concepts to non technical audiences. Implementing modern code development and MLOps strategies, in collaboration with Data Science and Data Engineering to support the proactive identification, targeting and resolution of any ML model(s) performance issues across their entire lifecycle. Developing operating More ❯