11 of 11 Keras Jobs in the Midlands

e.g. Kubeflow) - Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform - Working knowledge of one or more ML engineering frameworks (e.g. TensorFlow, PyTorch, Keras, Scikit-Learn) - Working knowledge of object-oriented programming and unit testing in Python - Working knowledge of application and information security principles and practices (e.g. OWASP for Machine Learning) - Working knowledge More ❯

e.g. Kubeflow) - Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform - Working knowledge of one or more ML engineering frameworks (e.g. TensorFlow, PyTorch, Keras, Scikit-Learn) - Working knowledge of object-oriented programming and unit testing in Python - Working knowledge of application and information security principles and practices (e.g. OWASP for Machine Learning) - Working knowledge More ❯

e.g. Kubeflow) - Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform - Working knowledge of one or more ML engineering frameworks (e.g. TensorFlow, PyTorch, Keras, Scikit-Learn) - Working knowledge of object-oriented programming and unit testing in Python - Working knowledge of application and information security principles and practices (e.g. OWASP for Machine Learning) - Working knowledge More ❯

e.g. Kubeflow) - Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform - Working knowledge of one or more ML engineering frameworks (e.g. TensorFlow, PyTorch, Keras, Scikit-Learn) - Working knowledge of object-oriented programming and unit testing in Python - Working knowledge of application and information security principles and practices (e.g. OWASP for Machine Learning) - Working knowledge More ❯

e.g. Kubeflow) - Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform - Working knowledge of one or more ML engineering frameworks (e.g. TensorFlow, PyTorch, Keras, Scikit-Learn) - Working knowledge of object-oriented programming and unit testing in Python - Working knowledge of application and information security principles and practices (e.g. OWASP for Machine Learning) - Working knowledge More ❯

e.g. Kubeflow) - Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform - Working knowledge of one or more ML engineering frameworks (e.g. TensorFlow, PyTorch, Keras, Scikit-Learn) - Working knowledge of object-oriented programming and unit testing in Python - Working knowledge of application and information security principles and practices (e.g. OWASP for Machine Learning) - Working knowledge More ❯

RFI/RFP process, as preferred bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms - demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning tools (e.g. Terraform). Technology deployment- proven More ❯

Get AI-powered advice on this job and more exclusive features. This range is provided by In Technology Group. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range More ❯

Python, R, SQL, and data processing frameworks (Spark, Hadoop, etc.) ML & Data Engineering pipelines Python with Django and Flask, Spark, Big-Data stack - Hive, Kafka & NoSQL ML Frameworks (like Keras or PyTorch) and libraries (like scikit-learn) Statistical Analysis and Fine-Tuning/Hyper-Tuning the models (like Spark-Trails, Optuna) Model Lifecycle management in ML Flow and Graph QL More ❯

Develop and deploy AI solutions using Azure Machine Learning services. Have a knowledge of top ML libraries scalable across multiple CPU’s and GPU’s. Such as TensorFlow, PyTorch, Keras, OpenAI, XGBoost. And have used these in a commercial setting. Troubleshoot and resolve issues related to data processing and AI model performance. Collaborate with cross-functional teams to understand data More ❯

Develop and deploy AI solutions using Azure Machine Learning services. Have a knowledge of top ML libraries scalable across multiple CPU’s and GPU’s. Such as TensorFlow, PyTorch, Keras, OpenAI, XGBoost. And have used these in a commercial setting. Troubleshoot and resolve issues related to data processing and AI model performance. Collaborate with cross-functional teams to understand data More ❯