1 to 25 of 53 Permanent MLOps Jobs in the East Midlands

with call/contact-centre analytics, Microsoft Teams Graph API, or telephony platforms (BroadWorks, Webex Calling). Knowledge of data governance, model ethics, and MLOps practices. Exposure to data visualization and predictive analytics for customer-experience metrics. Advanced degree in AI, ML, Data Science, or related discipline. ISTQB AI Testing ...

with call/contact-centre analytics, Microsoft Teams Graph API, or telephony platforms (BroadWorks, Webex Calling). Knowledge of data governance, model ethics, and MLOps practices. Exposure to data visualization and predictive analytics for customer-experience metrics. Advanced degree in AI, ML, Data Science, or related discipline. ISTQB AI Testing ...

with call/contact-centre analytics, Microsoft Teams Graph API, or telephony platforms (BroadWorks, Webex Calling). Knowledge of data governance, model ethics, and MLOps practices. Exposure to data visualization and predictive analytics for customer-experience metrics. Advanced degree in AI, ML, Data Science, or related discipline. ISTQB AI Testing ...

with call/contact-centre analytics, Microsoft Teams Graph API, or telephony platforms (BroadWorks, Webex Calling). Knowledge of data governance, model ethics, and MLOps practices. Exposure to data visualization and predictive analytics for customer-experience metrics. Advanced degree in AI, ML, Data Science, or related discipline. ISTQB AI Testing ...

Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps, or secure communications. Knowledge of ethics, bias mitigation, and fairness in AI. Familiarity with justice technology, corrections, or secure IT systems. Contributions to AI research ...

Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps, or secure communications. Knowledge of ethics, bias mitigation, and fairness in AI. Familiarity with justice technology, corrections, or secure IT systems. Contributions to AI research ...

Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps, or secure communications. Knowledge of ethics, bias mitigation, and fairness in AI. Familiarity with justice technology, corrections, or secure IT systems. Contributions to AI research ...

Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps, or secure communications. Knowledge of ethics, bias mitigation, and fairness in AI. Familiarity with justice technology, corrections, or secure IT systems. Contributions to AI research ...

Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps, or secure communications. Knowledge of ethics, bias mitigation, and fairness in AI. Familiarity with justice technology, corrections, or secure IT systems. Contributions to AI research ...

evaluation of new model architectures. · Implement production features end-to-end under guidance from senior engineers. · Participate in code reviews, testing, deployment, and MLOps workflows. · Work across internal products and contract-based venture projects. Requirements · Strong foundational programming skills in Python. · Basic understanding of AI/ML models ...

evaluation of new model architectures. · Implement production features end-to-end under guidance from senior engineers. · Participate in code reviews, testing, deployment, and MLOps workflows. · Work across internal products and contract-based venture projects. Requirements · Strong foundational programming skills in Python. · Basic understanding of AI/ML models ...

evaluation of new model architectures. · Implement production features end-to-end under guidance from senior engineers. · Participate in code reviews, testing, deployment, and MLOps workflows. · Work across internal products and contract-based venture projects. Requirements · Strong foundational programming skills in Python. · Basic understanding of AI/ML models ...

evaluation of new model architectures. · Implement production features end-to-end under guidance from senior engineers. · Participate in code reviews, testing, deployment, and MLOps workflows. · Work across internal products and contract-based venture projects. Requirements · Strong foundational programming skills in Python. · Basic understanding of AI/ML models ...

evaluation of new model architectures. · Implement production features end-to-end under guidance from senior engineers. · Participate in code reviews, testing, deployment, and MLOps workflows. · Work across internal products and contract-based venture projects. Requirements · Strong foundational programming skills in Python. · Basic understanding of AI/ML models ...

Familiar with Docker and CI/CD pipelines Experience with managed ML platforms such as SageMaker, Vertex AI or Azure ML Data engineering and MLOps Experience with data warehouses such as Snowflake, BigQuery or Redshift Workflow orchestration using tools like Airflow or Dagster Experience with MLOps tools such as MLflow ...

Familiar with Docker and CI/CD pipelines Experience with managed ML platforms such as SageMaker, Vertex AI or Azure ML Data engineering and MLOps Experience with data warehouses such as Snowflake, BigQuery or Redshift Workflow orchestration using tools like Airflow or Dagster Experience with MLOps tools such as MLflow ...

Familiar with Docker and CI/CD pipelines Experience with managed ML platforms such as SageMaker, Vertex AI or Azure ML Data engineering and MLOps Experience with data warehouses such as Snowflake, BigQuery or Redshift Workflow orchestration using tools like Airflow or Dagster Experience with MLOps tools such as MLflow ...

Familiar with Docker and CI/CD pipelines Experience with managed ML platforms such as SageMaker, Vertex AI or Azure ML Data engineering and MLOps Experience with data warehouses such as Snowflake, BigQuery or Redshift Workflow orchestration using tools like Airflow or Dagster Experience with MLOps tools such as MLflow ...

Familiar with Docker and CI/CD pipelines Experience with managed ML platforms such as SageMaker, Vertex AI or Azure ML Data engineering and MLOps Experience with data warehouses such as Snowflake, BigQuery or Redshift Workflow orchestration using tools like Airflow or Dagster Experience with MLOps tools such as MLflow ...

data ingestion and transformation pipelines. Work with structured and unstructured data from databases, APIs, and data lakes. Ensure data quality, reproducibility, and versioning. 4. MLOps & Automation Implement MLOps practices including CI/CD for ML, model versioning, and experiment tracking. Use tools such as MLflow, Kubeflow, SageMaker, Vertex ...

data ingestion and transformation pipelines. Work with structured and unstructured data from databases, APIs, and data lakes. Ensure data quality, reproducibility, and versioning. 4. MLOps & Automation Implement MLOps practices including CI/CD for ML, model versioning, and experiment tracking. Use tools such as MLflow, Kubeflow, SageMaker, Vertex ...

data ingestion and transformation pipelines. Work with structured and unstructured data from databases, APIs, and data lakes. Ensure data quality, reproducibility, and versioning. 4. MLOps & Automation Implement MLOps practices including CI/CD for ML, model versioning, and experiment tracking. Use tools such as MLflow, Kubeflow, SageMaker, Vertex ...

data ingestion and transformation pipelines. Work with structured and unstructured data from databases, APIs, and data lakes. Ensure data quality, reproducibility, and versioning. 4. MLOps & Automation Implement MLOps practices including CI/CD for ML, model versioning, and experiment tracking. Use tools such as MLflow, Kubeflow, SageMaker, Vertex ...

data ingestion and transformation pipelines. Work with structured and unstructured data from databases, APIs, and data lakes. Ensure data quality, reproducibility, and versioning. 4. MLOps & Automation Implement MLOps practices including CI/CD for ML, model versioning, and experiment tracking. Use tools such as MLflow, Kubeflow, SageMaker, Vertex ...

first centralised data platform, with a clear focus on enabling AI development rather than analytics or BI. Working closely with AI Engineers and MLOps Engineers, you'll ensure datasets are structured, versioned and reproducible so models can be trained, evaluated, monitored and retrained reliably. This role is hands … lifecycle management Supporting AI teams with training, validation and test data splits Embedding data quality checks, monitoring, lineage and drift detection Working closely with MLOps to support model monitoring and retraining Ensuring data privacy, security and compliance are built in from day one Using infrastructure-as-code and CI/ ...