1 to 25 of 56 TensorFlow Jobs in the South East

experience developing and deploying machine learning and generative AI solutions in production environments. * Strong Python engineering skills with experience using frameworks such as PyTorch, TensorFlow, LangChain, or similar. * Experience working with LLMs, prompt engineering, vector databases, and retrieval augmented generation (RAG) architectures. * Strong knowledge of cloud platforms including ...

solutions in Python Solid understanding of the Python ML ecosystem including libraries such as NumPy, pandas, and scikit learn, with exposure to PyTorch or TensorFlow Experience building and deploying containerised services and APIs Working knowledge of SQL and data driven application development Hands on experience with at least ...

delivering AI/ML projects end-to-end in production environments Strong Python skills with hands-on use of ML libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) with ...

MLflow, Azure ML, Azure DevOps, or similar tools. Strong programming skills in Python and familiarity with common ML/AI libraries, including Scikit-learn, TensorFlow, and Keras. Experience implementing machine learning and large language models, including deployment, monitoring, and retraining. Familiarity with software engineering guidelines, including version control ...

such as OpenAI, Hugging Face, or similar Experience building and integrating AI-powered solutions into production systems Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar Familiarity with APIs, microservices, and cloud platforms (Azure, AWS, or GCP) Experience handling and processing large datasets Knowledge of prompt engineering ...

date with the latest ML/AI research and incorporate cutting-edge techniques and frameworks when applicable. Utilize ML libraries and tools such as TensorFlow, PyTorch, Scikit-learn, XGBoost, and others for model building and experimentation. Ensure machine learning solutions are scalable and optimized for performance on large datasets ...

with experience handling diverse datasets (tabular, computer vision, point cloud, game data). Proficient with ML frameworks (NumPy, OpenCV, scikit‐learn, PyTorch/PyTorch3D, TensorFlow, Keras). Experience with CI/CD pipelines, version control (GitLab, Perforce), cloud platforms (preferably AWS) and scalable deployment workflows. Outstanding problem‐solving ...

sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model serving." End-to-end" MLOps "experience, including CI/CD for ML, experiment tracking, model registries ...