6 of 6 Remote/Hybrid Permanent Keras Jobs

Proficient in programming languages such as Python and familiar with major Data Science/machine learning libraries like OpenCV, scikit-learn, PyTorch, TensorFlow/Keras, and Pandas. Demonstrated ability to develop and test code within cloud environments. Experience with large datasets and developing in cloud computing platforms such ...

Linux, Docker. Plus, a strong opinion on your IDE/editor of choice is welcome ;) Familiarity with modern machine learning tools, for instance TensorFlow, Keras, PyTorch or SKLearn. Commercial experience with these is not essential. You should be aware of the broad landscape of machine learning applications, tools, and technologies ...

Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex ...

Birmingham, United Kingdom/Brighton, United Kingdom/Bristol, United Kingdom/Cardiff, United Kingdom/Glasgow, United Kingdom/London, United Kingdom/Manchester, United Kingdom/Newcastle Upon Tyne, United Kingdom Location/ ...

We are an AI-led, platform-driven Digital Engineering and Enterprise Modernization partner, combining deep technical expertise and industry experience to help our clients anticipate what’s next. Our offerings and proven solutions create a ...

environment with sensitive data. You’ll work with engineering to move models from idea to production. Tech Stack: Python, scikit-learn, PyTorch, TensorFlow/Keras, LangChain, Pydantic, Spark, Kafka, Databricks, MLflow, Azure, Docker, Kubernetes. Salary: Up to £100k Working Environment: Fully Remote in UK What you’ll do Research, prototype … deploy LLM use cases (Q&A, summarisation, document processing) Build and tune models using scikit-learn, PyTorch, TensorFlow/Keras, and XGBoost Create data pipelines for batch and streaming with Spark and Kafka Use Databricks and MLflow for experiments, deployment, and monitoring What you’ll bring Hands-on Python ...