26 to 33 of 33 Keras Jobs

with AI systems, machine learning models, or related technologies using Microsoft AI tools and Azure. Technical Skills Needed Familiarity with AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, Keras). Experience in Microsoft Azure as well as Microsoft AI tools (Copilot) is a must. Proficient in programming languages such as Python, Java, or C++. Understanding of system architecture and More ❯

enabling efficient data transformation for downstream machine learning modeling and analysis. 3. Utilize knowledge of advanced data science techniques and tools, including Python, Apache Spark, SparkML, scikit-learn, TensorFlow, Keras, XGBoost, and Tidyverse, to build various ML-driven applications such as recommendation models, timeseries forecasting, attribution models that address business needs and deliver impactful solutions. 4. Utilize knowledge of AWS … large-scale data processing, enabling seamless preparation for downstream modeling and analysis. 10. Utilize Python, machine learning, supervised and unsupervised algorithms, and statistical modeling with SparkML, scikit-learn, TensorFlow, Keras, XGBoost, and Tidyverse to build large-scale machine learning models for clustering, segmentation, cancer detection, etc. 11. Utilize AWS SageMaker and Google Cloud Platform for scalable batch inferencing and modeling More ❯

to make an immediate contribution and strengthen their profile in AI for neurotechnology through impactful short-term work. - AI/ML research, particularly deep learning using platforms such as Keras, PyTorch, or TensorFlow - Developing and testing novel or customised AI models for complex, noisy, real-world datasets - Software optimisation for high-performance computing on CPU and GPU clusters - VR/ More ❯

to make an immediate contribution and strengthen their profile in AI for neurotechnology through impactful short-term work. - AI/ML research, particularly deep learning using platforms such as Keras, PyTorch, or TensorFlow - Developing and testing novel or customised AI models for complex, noisy, real-world datasets - Software optimisation for high-performance computing on CPU and GPU clusters - VR/ More ❯

to make an immediate contribution and strengthen their profile in AI for neurotechnology through impactful short-term work. - AI/ML research, particularly deep learning using platforms such as Keras, PyTorch, or TensorFlow - Developing and testing novel or customised AI models for complex, noisy, real-world datasets - Software optimisation for high-performance computing on CPU and GPU clusters - VR/ More ❯

to make an immediate contribution and strengthen their profile in AI for neurotechnology through impactful short-term work. - AI/ML research, particularly deep learning using platforms such as Keras, PyTorch, or TensorFlow - Developing and testing novel or customised AI models for complex, noisy, real-world datasets - Software optimisation for high-performance computing on CPU and GPU clusters - VR/ More ❯

team members in identifying and addressing data science opportunities. Required Skills & Experience Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using … problem-solving skills and ability to work independently or in a team. Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using More ❯

LLM features in a regulated 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, and 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 for data science and ML Practical experience with LLM frameworks (e.g. LangChain) Familiar with Spark More ❯