1 to 25 of 40 Permanent MLOps Jobs in the South West

production-ready systems. Academic Foundation Bachelors or Masters degree in Computer Science, Machine Learning, Engineering , or a closely related discipline. Bonus Points Experience with MLOps and model serving platforms such as BentoML, MLflow, or SageMaker . Hands-on work with streaming and batch data pipelines using tools like Spark, Airflow ...

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

Architect secure, scalable GenAI solutions on AWS and GCP Build APIs, services, and pipelines to integrate GenAI into real business workflows Apply LLMOps/MLOps practices : versioning, monitoring, cost control, bias, and drift management Work directly with clients to translate business problems into deployable AI solutions , not slide decks Contribute ...

Contract MLOps Engineer | MLflow | Databricks | Production ML Duration: Initially 3 months Day rate: £500 - £550, Inside IR35 Workplace: Remote, with occasional travel to client-site Inara are supporting a consultancy-led team delivering production-grade machine learning platforms for a range of end clients, and they're looking … senior, hands-on Contract MLOps Engineer to help take ML systems from experimentation into reliable, scalable production. This role is firmly focused on ML enablement and platform engineering rather than model research. You'll be the person ensuring models can be trained, tracked, deployed, governed, and monitored properly in real ...

Contract MLOps Engineer | MLflow | Databricks | Production ML Duration: Initially 3 months Day rate: £500 - £550, Inside IR35 Workplace: Remote, with occasional travel to client-site Inara are supporting a consultancy-led team delivering production-grade machine learning platforms for a range of end clients, and they're looking … senior, hands-on Contract MLOps Engineer to help take ML systems from experimentation into reliable, scalable production. This role is firmly focused on ML enablement and platform engineering rather than model research. You'll be the person ensuring models can be trained, tracked, deployed, governed, and monitored properly in real ...

Contract MLOps Engineer | MLflow | Databricks | Production ML Duration: Initially 3 months Day rate: £500 - £550, Inside IR35 Workplace: Remote, with occasional travel to client-site Inara are supporting a consultancy-led team delivering production-grade machine learning platforms for a range of end clients, and they're looking … senior, hands-on Contract MLOps Engineer to help take ML systems from experimentation into reliable, scalable production. This role is firmly focused on ML enablement and platform engineering rather than model research. You'll be the person ensuring models can be trained, tracked, deployed, governed, and monitored properly in real ...

Contract MLOps Engineer | MLflow | Databricks | Production ML Duration: Initially 3 months Day rate: £500 - £550, Inside IR35 Workplace: Remote, with occasional travel to client-site Inara are supporting a consultancy-led team delivering production-grade machine learning platforms for a range of end clients, and they're looking … senior, hands-on Contract MLOps Engineer to help take ML systems from experimentation into reliable, scalable production. This role is firmly focused on ML enablement and platform engineering rather than model research. You'll be the person ensuring models can be trained, tracked, deployed, governed, and monitored properly in real ...

Contract MLOps Engineer | MLflow | Databricks | Production ML Duration: Initially 3 months Day rate: £500 - £550, Inside IR35 Workplace: Remote, with occasional travel to client-site Inara are supporting a consultancy-led team delivering production-grade machine learning platforms for a range of end clients, and they're looking … senior, hands-on Contract MLOps Engineer to help take ML systems from experimentation into reliable, scalable production. This role is firmly focused on ML enablement and platform engineering rather than model research. You'll be the person ensuring models can be trained, tracked, deployed, governed, and monitored properly in real ...

Contract MLOps Engineer | MLflow | Databricks | Production ML Duration: Initially 3 months Day rate: £500 - £550, Inside IR35 Workplace: Remote, with occasional travel to client-site Inara are supporting a consultancy-led team delivering production-grade machine learning platforms for a range of end clients, and they're looking … senior, hands-on Contract MLOps Engineer to help take ML systems from experimentation into reliable, scalable production. This role is firmly focused on ML enablement and platform engineering rather than model research. You'll be the person ensuring models can be trained, tracked, deployed, governed, and monitored properly in real ...

teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support model monitoring, drift detection, and ongoing optimisation Required Experience Proven commercial experience as a Machine Learning Engineer … with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35 ...

teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support model monitoring, drift detection, and ongoing optimisation Required Experience Proven commercial experience as a Machine Learning Engineer … with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35 ...

teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support model monitoring, drift detection, and ongoing optimisation Required Experience Proven commercial experience as a Machine Learning Engineer … with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35 ...

teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support model monitoring, drift detection, and ongoing optimisation Required Experience Proven commercial experience as a Machine Learning Engineer … with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35 ...

teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support model monitoring, drift detection, and ongoing optimisation Required Experience Proven commercial experience as a Machine Learning Engineer … with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35 ...

teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support model monitoring, drift detection, and ongoing optimisation Required Experience Proven commercial experience as a Machine Learning Engineer … with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35 ...

approaches into production, including deployment and monitoring Build and optimise ML pipelines on AWS Develop LLM-powered solutions, including evaluation and observability Apply strong MLOps practices: experiment tracking, versioning, and reproducibility Communicate findings clearly to technical and non-technical stakeholders Mentor junior engineers and contribute to team best practices This … TensorFlow) Production experience with AWS ML services (e.g. SageMaker, Lambda, S3) Proven ability to move models from experimentation into live systems Experience with MLOps tools (MLflow, Weights & Biases, DVC, or similar) Hands-on exposure to LLM/GenAI applications, including RAG Nice to have: Experience with advanced LLM techniques (e.g. ...

transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable … strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including ...

transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable … strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including ...

transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable … strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including ...

transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low l atency , highly reliable … strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices. Proven technical leadership experience including ...