19 of 19 Remote Keras Jobs

techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and More ❯

techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and More ❯

techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and More ❯

techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and More ❯

techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and More ❯

and techniques, such as supervised. and unsupervised learning, transformer models, deep learning, computer vision, natural language processing, etc. Experience with common ML libraries and frameworks such as TensorFlow, PyTorch, Keras, Scikit-learn. Ability to work independently and collaboratively with multi-functional teams with excellent communication and presentation skills. Experience in writing unit tests and documentation for ML code. Familiarity with More ❯

Previous experience developing underwriting or behavioural models for credit extension Desired: Master's degree in Data Science/Machine Learning or related discipline Knowledge of Deep Learning frameworks, ideally Keras/Tensorflow Familiarity with software version control (GitHub, bitbucket) Knowledge of Tableau Ability to comprehend research papers and possibly apply their solutions Credit card industry knowledge What's in it More ❯

have tangible, high-profile impact. Essential experience: Strong background in Computer Vision and image/video processingHands-on experience with OpenCV pipelines Proficiency with deep learning frameworks (PyTorch, TensorFlow, Keras)Knowledge of CNN architectures and training dynamicsProven experience deploying and optimizing models for real-time applicationsStrong data science and metrics literacy Nice to have: PhD or Master's in Computer More ❯

tangible, high-profile impact. Essential experience: Strong background in Computer Vision and image/video processing Hands-on experience with OpenCV pipelines Proficiency with deep learning frameworks (PyTorch, TensorFlow, Keras) Knowledge of CNN architectures and training dynamics Proven experience deploying and optimizing models for real-time applications Strong data science and metrics literacy Nice to have: PhD or Master's More ❯

to help us identify, diagnose, and cure production inefficiencies using data. Specific responsibilities include: Model Development : Design and develop deep learning models using frameworks such as TensorFlow, PyTorch, and Keras for specific applications in the manufacturing domain. Training and Evaluation : Train models on large datasets, evaluate their performance, and fine-tune hyperparameters to optimize results. Deployment : Implement and deploy models More ❯

Ability to communicate clearly across technical and non-technical teams Strong data visualisation skills — ideas that land Nice to Have Background in credit cards or consumer lending Deep learning (Keras, TensorFlow) Git, Tableau, Bitbucket MSc in Data Science or similar Why Apply? Excellent salary + benefits 25–30 days holiday + birthday off Hybrid working (London) Family friendly policies Great More ❯

Ability to communicate clearly across technical and non-technical teams Strong data visualisation skills — ideas that land Nice to Have Background in credit cards or consumer lending Deep learning (Keras, TensorFlow) Git, Tableau, Bitbucket MSc in Data Science or similar Why Apply? Excellent salary + benefits 25–30 days holiday + birthday off Hybrid working (London) Family friendly policies Great More ❯

Ability to communicate clearly across technical and non-technical teams Strong data visualisation skills — ideas that land Nice to Have Background in credit cards or consumer lending Deep learning (Keras, TensorFlow) Git, Tableau, Bitbucket MSc in Data Science or similar Why Apply? Excellent salary + benefits 25–30 days holiday + birthday off Hybrid working (London) Family friendly policies Great More ❯

Ability to communicate clearly across technical and non-technical teams Strong data visualisation skills — ideas that land Nice to Have Background in credit cards or consumer lending Deep learning (Keras, TensorFlow) Git, Tableau, Bitbucket MSc in Data Science or similar Why Apply? Excellent salary + benefits 25–30 days holiday + birthday off Hybrid working (London) Family friendly policies Great More ❯

Ability to communicate clearly across technical and non-technical teams Strong data visualisation skills — ideas that land Nice to Have Background in credit cards or consumer lending Deep learning (Keras, TensorFlow) Git, Tableau, Bitbucket MSc in Data Science or similar Why Apply? Excellent salary + benefits 25–30 days holiday + birthday off Hybrid working (London) Family friendly policies Great More ❯

foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series forecasting). Practical experience with Keras or PyTorch is required. Full-Stack Deployment: Demonstrable experience taking models to production, including building and deploying APIs with FastAPI and using Vertex AI for ML workflows. Visualization & Communication: Ability More ❯

MLOps suite including Vertex Pipelines (or similar platforms). Technical Proficiency: in SQL and Python, along with familiarity with standard libraries used in data science such as scikit-learn, Keras, TensorFlow, pandas, NumPy, seaborn, and Matplotlib. Desirables: While not essential, the following experience would be highly beneficial: Production Experience with LLM Monitoring: Hands-on experience with monitoring LLMs in production More ❯

regulated environment: medical, aerospace, or automotive Experience of real-time operating systems and embedded development Experience working to an Agile lifecycle. Awareness of machine-learning frameworks such as Pytorch, Keras/Tensorflow, MATLAB Machine Learning toolbox Awareness of mathematical libraries used for signal processing, image processing and data processing Awareness of high-performance computing and the challenges of parallel processing More ❯

software engineering and algorithm development skills in Python, including advanced image processing for 3D datasets, and ideally interpretation of biological (not medical) data from time series microscopy. Likely TensorFlow, Keras, PyLattice or similar. Ideally use of machine learning, neural networks, particularly CNNs given the data involved, feature extraction and tracking. Familiarity with computer vision, cellular imaging, volumetric tiling, voxel imaging More ❯