151 to 175 of 274 TensorFlow Jobs in England

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 ...

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 ...

with team members in diverse fields Strong programming abilities in Python, and extensive experience with the scientific and machine-learning stack: Numpy, Torch/Tensorflow/Jax, Scikit-learn, Polars, SQL Expertise with deep learning approaches such as diffusion or flow matching Proficiency in modern software development practices: code ...